Proficient in Python, Node.js (or Java), and React (preferred). Experience with AWS Services: S3, Lambda, DynamoDB, Bedrock, Textract, RDS, Fargate. Experience in LLM-based application development (LangChain, Bedrock, or OpenAI APIs). Strong in NLP and embeddings (via SageMaker or third-party APIs like Cohere, Hugging Face). Knowledge of vector databases (Pinecone, ChromaDB, OpenSearch, etc.). Familiar with containerization (Docker, ECS/Fargate). Excellent understanding of REST API design and security. Experience handling PDF/image-based document classification. Good SQL and NoSQL skills (MS SQL, MongoDB). Preferred Qualifications: AWS Certified – especially in AI/ML or Developer Associate. Job Types: Full-time, Fresher, Internship Pay: ₹554,144.65 - ₹1,500,000.00 per year Schedule: Day shift Morning shift Supplemental Pay: Performance bonus Ability to commute/relocate: Ahmedabad, Gujarat: Reliably commute or planning to relocate before starting work (Preferred) Work Location: In person

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Job Title: Senior Python Developer (4–6 Years Experience) Location: Gurgaon Job Type: Full-Time – WFO About the Role: We are seeking a skilled and motivated Senior Python Developer with 4–6 years of experience and a B.Tech in CSE or IT. You’ll design, develop, and maintain scalable applications, working within an Agile team and collaborating across functions. Key Responsibilities: Design, write, and maintain efficient, scalable Python code. Collaborate with product managers, designers, and developers. Build and integrate RESTful APIs and microservices. Conduct code reviews and ensure best practices. Work with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB). Debug, optimize, and contribute to architecture and performance. Write unit/integration tests and explore new technologies. Mentor junior developers and participate in Agile ceremonies. Required Skills & Qualifications: B.Tech in CSE, IT, or related field. 4–6 years of Python development experience. Proficient in Django, Flask, or FastAPI. Solid understanding of OOP, data structures, and algorithms. Experience with AWS/GCP/Azure, Docker, Git, CI/CD. Skilled in writing clean, maintainable code. Strong communication and Agile collaboration skills. Nice-to-Have Skills: Knowledge of React/Angular, Kubernetes, RabbitMQ/Kafka. Familiarity with GraphQL, ML, or data science concepts. Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

About the Role As the Head - Procurement at Neysa.ai, you will build and lead a high-impact, modern procurement function from the ground up—crafting sourcing strategies, vendor partnerships, and operational systems that power our AI-first and cloud-native future. This role is both strategic and operational. You’ll be responsible for shaping Neysa’s sourcing roadmap across complex categories like compute infrastructure (GPUs, servers), cloud credits, SaaS tools, professional services, and specialized AI partnerships. In a fast-moving ecosystem where scale and agility are paramount, you’ll bring clarity, control, and commercial advantage to every procurement decision. You’ll work closely with business, engineering, and finance leaders to forecast needs, optimize cost structures, ensure compliance, and deliver long-term value through data-driven sourcing and negotiation strategies. If you’re excited by the challenge of building procurement in a high-growth AI tech company—this is your opportunity to lead from the front. Key Responsibilities 1. Strategic Sourcing & Category Ownership Build and execute Neysa’s end-to-end procurement strategy across CapEx and OpEx. Lead sourcing for high-priority categories: GPUs, cloud credits, servers, networking equipments, SaaS platforms, and consulting services. Define procurement policies and build lightweight, scalable governance frameworks that balance structure with agility. Forecast category demand in partnership with all functional teams. Manage and mentor procurement teams, fostering a culture of innovation and continuous improvement 2. Vendor & Ecosystem Management Identify, evaluate, and engage with high-value strategic partners, global suppliers, and niche vendors. Lead commercial negotiations, pricing discussions, and contract finalisation with a focus on TCO and flexibility. Establish vendor scorecards and feedback loops for ongoing performance management. Develop alternate supplier strategies to mitigate risks and ensure continuity. 3. Procurement Intelligence, Digitisation & Compliance Implement procurement automation through ERP or lightweight tools; explore AI-led platforms to drive efficiencies. Build real-time dashboards and spend visibility systems for Finance and leadership. Partner with Legal and Finance to ensure regulatory compliance, risk mitigation, and audit readiness. Drive data-backed insights into sourcing decisions and identify cost-saving opportunities. 4. Build-Mode Leadership As the first procurement leader at Neysa, you’ll operate as a strategic individual contributor with the mandate to build a scalable function. Design scalable SOPs, documentation processes, and vendor onboarding play books. Responsible for scaling procurement operations across geographies and verticals. Reporting to: Executive Vice President – Finance (EVP - Finance) Functionally Aligned With: Leadership team What You Bring 15+ years of procurement experience in tech, cloud, datacenter or high-growth enterprise environments. Proven ability to handle strategic sourcing in areas like cloud infra, SaaS, hardware, and AI/ML services. Strong commercial acumen with expertise in negotiation, contract structuring, and vendor governance. Excellent analytical, organisational, and communication skills to articulate complex technical and procurement strategies. Experience in scaling procurement systems using ERP tools (SAP, Oracle, Coupa, etc.) or modern procurement stacks. Deep understanding of the tech vendor ecosystem and regulatory frameworks around high-value sourcing. Bias for action, builder’s mindset, and a pragmatic approach to working in evolving environments. Why Join Neysa? Neysa.ai is reimagining how businesses build and deploy AI at scale—and your role will directly impact how efficiently we operate, partner, and scale in this journey. This is your chance to build a procurement function that’s not just operational but transformational. You’ll have the runway to make critical sourcing decisions, influence long-term vendor strategy, and eventually build a procurement team from scratch. If you want to create tangible impact at the intersection of AI, cloud, and commercial excellence—this is the role for you. Build the backbone of AI acceleration. Build it at Neysa. www.neysa.ai Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 7.00 + years Salary : INR 4000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: MatchMove) (*Note: This is a requirement for one of Uplers' client - MatchMove) What do you need for this opportunity? Must have skills required: Gen AI, AWS data stack, Kinesis, open table format, Pyspark, stream processing, Kafka, MySQL, Python MatchMove is Looking for: Technical Lead - Data Platform Data, you will architect, implement, and scale our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS. You will lead a small team of engineers while working cross-functionally with stakeholders from fraud, finance, product, and engineering to enable reliable, timely, and secure data access across the business. You will champion best practices in data design, governance, and observability, while leveraging GenAI tools to improve engineering productivity and accelerate time to insight. You will contribute to Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services. Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark. Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services. Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases. Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment. Collaborating with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance (GDPR, MAS TRM). Using Generative AI tools to enhance developer productivity — including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights. Mentoring data engineers, setting technical direction, and ensuring delivery of high-quality, observable data pipelines. Responsibilities:: Architect scalable, cost-optimized pipelines across real-time and batch paradigms, using tools such as AWS Glue, Step Functions, Airflow, or EMR. Manage ingestion from transactional sources using AWS DMS, with a focus on schema drift handling and low-latency replication. Design efficient partitioning, compression, and metadata strategies for Iceberg or Hudi tables stored in S3, and cataloged with Glue and Lake Formation. Build data marts, audit views, and analytics layers that support both machine-driven processes (e.g. fraud engines) and human-readable interfaces (e.g. dashboards). Ensure robust data observability with metrics, alerting, and lineage tracking via OpenLineage or Great Expectations. Lead quarterly reviews of data cost, performance, schema evolution, and architecture design with stakeholders and senior leadership. Enforce version control, CI/CD, and infrastructure-as-code practices using GitOps and tools like Terraform. Requirements At-least 7 years of experience in data engineering. Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs. Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation. Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions. Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments. Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene. Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders. Brownie Points:: Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements. Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection. Familiarity with data contracts, data mesh patterns, and data as a product principles. Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases. Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3. Experience building data platforms for ML/AI teams or integrating with model feature stores. Engagement Model: : Direct placement with client This is remote role Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: ML, Python Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less