23 Llm Apis Jobs

Role: DevOps Open-AI Azure Location: Bangalore, Chennai, Pune, Hyderabad. Work mode: Hybrid Exp: 9+ Required Qualifications: Bachelors degree in Computer Science, Engineering, or a related technical field (or equivalent experience). 8+ years of experience in DevOps, SRE, or Cloud Engineering roles. Strong expertise with Azure cloud services and automation tools. Proficient in Infrastructure as Code (Terraform, Bicep, ARM). Deep understanding of CI/CD tools and methodologies. Experience managing data pipelines and distributed systems in production environments. Familiarity with AI/ML workflows, including vector databases and LLM APIs. Proficient in scripting languages such as Python, Bash, or PowerShell. if you are interested, please share updated resume to [HIDDEN TEXT] Show more Show less

You will be responsible for developing clean and modular Python code for scalable data pipelines. Your role will involve using Pandas to drive data transformation and analysis workflows. Additionally, you will be required to integrate with LLM APIs such as OpenAI to build smart document solutions. Building robust REST APIs using FastAPI or Flask for data and document services will be a key aspect of this role. Experience working with Azure cloud services like Functions, Blob, and App Services is necessary. An added bonus would be the ability to integrate with MongoDB and support document workflows. This is a contract-to-hire position based in Gurgaon, with a duration of 6 months and following IST shift timings.,

You will be joining Jetbro, a dynamic digital agency that specializes in bespoke development solutions for websites, mobile applications, and business applications. The company is at the forefront of AI-driven projects, offering innovative and cutting-edge solutions to its clients. As the company continues to expand, they are looking for a skilled AI Engineer to build and maintain high-performance, scalable systems. Your responsibilities will include integrating and orchestrating OpenAI, Gemini, and other LLM APIs to power features such as Essay & Recommendation Brainstorming (Voice & Text), AI-driven Evaluation and Scoring, and Contextual, voice-based guidance via Ivy (Text-to-Speech + prompt control). You will also be tasked with building and fine-tuning prompt-response workflows, input-output schemas, fallback handling, and session management. Additionally, you will need to convert speech inputs to structured text using Speech-to-Text APIs, and implement Text-to-Speech outputs for voice-based interactions. Setting up and managing Vector Databases (e.g., Pinecone, Weaviate, AstraDB) to store and retrieve semantically indexed essay data will also be part of your role. Collaboration with backend, frontend, and QA teams to ensure smooth flow of AI-driven features across the platform is essential. Furthermore, you will be responsible for evaluating and continuously improving AI output quality by testing prompt variations and refining scoring logic. Mandatory requirements for this position include 1.5 years of hands-on experience building with LLM APIs (OpenAI, Gemini, Claude, etc.), a strong grasp of prompt engineering, including role prompting, temperature control, and context design, experience working with Python and integrating APIs in live products, familiarity with Text-to-Speech and Speech-to-Text workflows (OpenAI Whisper, Google Cloud STT/TTS, etc.), exposure to using or querying Vector Databases (e.g., Pinecone or similar), and basic understanding of AI evaluation techniques (prompt tuning, hallucination handling, response scoring). Good to have qualifications include experience with LangChain, LlamaIndex, or agent frameworks, working knowledge of FastAPI or Django to support backend integration, familiarity with Voice UX or chatbot design, comfort with versioning tools (Git), JSON handling, and API testing tools (Postman), and demonstrated ability to iterate quickly and adapt to changing LLM capabilities. In return, you can expect to work on mission-critical, real-world projects that impact large-scale operations at Jetbro. The company has a lean, no-nonsense tech culture built on ownership, accountability, and growth, with direct access to decision-makers and no red tape. You will enjoy flexibility in work location and timings, regular feedback, performance reviews, and learning opportunities.,

You are a skilled Data Engineer / AI/ML Developer with a strong expertise in Python and AI/ML, responsible for building and scaling production-grade systems using LLMs. Your role involves working on real-world AI integrations, APIs, and cloud deployments within a fast-paced, growth-focused team. Your key responsibilities include building AI/LLM systems using OpenAI, Anthropic, etc., working with frameworks like LangChain, CrewAI, or AutoGen, developing APIs with Flask/FastAPI and async patterns, integrating databases (PostgreSQL/MySQL) and REST APIs, deploying on AWS, GCP, or Azure, writing clean, testable, production-grade Python code, and translating business needs into technical solutions. To excel in this role, you must have 2+ years of experience with LLM APIs and 1+ AI project in production, 3+ years of Python development experience, familiarity with function calling, prompt design (ReAct, CoT), cloud deployment (any platform), Git workflows, and testing. Additionally, you should possess strong debugging, error handling, and system design skills, along with the ability to work independently and collaborate cross-functionally. A preferred background would include a degree in CS or equivalent experience (bootcamp, self-taught, etc.), along with a portfolio showcasing live AI projects or GitHub repos. Knowledge of Vector DBs (Pinecone/Weaviate), Docker, and exposure to fintech would be considered as a bonus. Cloud or AI certifications, as well as experience in fintech or data-heavy domains, are nice-to-have skills for this role.,

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify peoples lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusigns Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you&aposll do We are looking for a Senior Full Stack Engineer with a deep understanding of both front-end and back-end technologies to help design, build, and maintain complex web applications. The ideal candidate will have extensive experience in creating scalable and high-performance web solutions, as well as a passion for learning new technologies and solving problems. You will collaborate with multi-functional teams to develop and implement innovative software solutions that meet our business needs. This position is an individual contributor role reporting to the Senior Manager, GTM Engineering. Responsibility Drive full-stack development of internal applications, primarily using TypeScript, React, and Node.js Collaborate with stakeholders to design scalable, maintainable, and user-friendly solutions Contribute to technical architecture decisions, service integration patterns, and engineering standards Implement REST and GraphQL APIs for interfacing with Salesforce, Jira, GitHub, and other enterprise systems Uphold high standards in code quality, testing, performance, and observability Guide peers and junior developers to foster collaboration and knowledge sharing Support backlog grooming, estimation, and agile planning Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position&aposs job designation depending on business needs and as permitted by local law. What you bring Basic 6+ years of experience in software engineering, with strong full-stack skills Proficiency in React, TypeScript, and Node.js with a deep understanding of modern front-end and back-end frameworks Experience integrating with SaaS platforms like Salesforce, Jira, GitHub, or similar systems via APIs Preferred Strong understanding of CI/CD practices, GitHub workflows, and automated testing frameworks Excellent communication skills with the ability to collaborate cross-functionally Familiarity with AI integration patterns, LLM APIs, or Retrieval-Augmented Generation (RAG) systems Experience working within Enterprise Applications, Business Systems, or GTM domains Exposure to cloud platforms (AWS preferred), containerization (Docker), and infrastructure-as-code Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do whats right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, youll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at [HIDDEN TEXT]. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at [HIDDEN TEXT] for assistance. Applicant and Candidate Privacy Notice Show more Show less

Who are we: Turbostart is not just a startup fund and accelerator, we are a catalyst for builders and a powerhouse of innovation. Our mission is to propel early-stage startups into the future by providing unparalleled support in technology, marketing, strategy, and beyond. We&aposre in the business of building tomorrow&aposs leaders - today. After 5 Years and 5 Funds we have supported over 50 startups, spanning sectors, stages and geographies - and this is just the beginning! Turbostart spans India, the Middle East, the US as well as Singapore - giving you the opportunity to gain exposure and see the impact of your work ripple across regions. Turbostart has also launched 5 Centers of Excellence across Tech, Marketing, Sales, UI/UX and Investment Banking to support the growth of our startup network. Know more about us on https://turbostart.co/ Turbostart Technology Development Centre (T2C), Turbostarts Tech Centre of Excellence gives you the opportunity to be part of the evolution of cutting edge technology solution development across multiple domains including EdTech, Fintech, Supply Chain / Logistics and Media / Entertainment. We have a laser focused approach on innovation and collaboration backed by strong objective R&D, futuristic and highly agile models for solution development, collaboration and engagement. Join us to be part of the unique mix of a corporate work environment (process driven ) that is focused on building new age solutions for startups that require extreme pace of innovation, agility and rapid engineering approaches. Know more about us on https://tsquaredc.com/ We are looking for sharp energetic minds to join our rapidly growing ecosystem and help take Turbostart to new heights! What we are looking for: Role: Full Stack Engineer As a Full Stack Developer at T2C, you will be responsible for designing, building and optimizing high-performance software solutions for real world problems across different industries. You will be working closely with startup founders, product managers, UI/UX designers and other engineers to shape the products of tomorrow. We use a wide range of programming languages, frameworks and libraries that suit the nature of the problem we try to solve. We are looking for engineers with a good aptitude, curiosity, creativity, good communication skills, quick learning abilities and most importantly share a passion for problem solving. Location: Kolkata, West Bengal, India Experience Required: 2-6 years What youll do: Develop and maintain responsive, dynamic, and scalable front-end applications using Python (Flask/FastAPI), React.js, Next.js, and TypeScript. Build Node (express) or Python (flask, fast api etc) microservices in a secure, scalable manner Design and Architect databases like MongoDB, Postgres, Firebase/Firestore etc Find solutions for problems using LLM APIs like Gemini, Deepseek, OpenAI etc Deploy software solutions to cloud platforms like GCP, AWS or Azure. Optimize applications for speed, scalability, and cross-browser compatibility. Design and build scalable software solutions using system design components like Queues and Caches. Our ideal candidate: 2+ years of hands-on experience developing scalable web applications with a strong focus on Python, using frameworks such as Flask or FastAPI. Proficiency in building RESTful APIs and microservices that are secure, efficient, and production-ready. Strong understanding of database design and optimization, with experience in PostgreSQL, MongoDB, or Firebase/Firestore, including indexing, schema design, and query performance tuning. Solid foundation in frontend technologies including React.js, Next.js, TypeScript, JavaScript (ES6+), HTML5, and CSS3, with familiarity in modern UI frameworks and responsive design principles. Experience with state management libraries such as Redux, Recoil, or Zustand, and a modular, component-based approach to UI development. Skilled in integrating REST APIs, GraphQL, and WebSockets, ensuring smooth data exchange between frontend and backend services. Exposure to cloud platforms like AWS, GCP, or Azure, along with practical knowledge of Docker for containerization and basic familiarity with Kubernetes for orchestration. Experience working with LLM APIs (e.g., OpenAI, Gemini, DeepSeek) to integrate AI/ML-driven features into applications is a strong plus. Strong problem-solving mindset with the ability to design and implement scalable, performant system architectures, including use of queues, caching mechanisms, and asynchronous processing. Familiarity with Git, CI/CD pipelines, Agile workflows, and a commitment to writing clean, maintainable code following industry best practices. Why join us Work on cutting-edge projects with early-stage startups solving real-world problems across industries like EdTech, FinTech, MarketingTech, Logistics, and Media. Be part of a global innovation ecosystem, collaborating with startup founders, product managers, and domain experts. Continuous learning & mentorship from top-tier tech experts across Turbostarts Centres of Excellence. Access to the latest tools & frameworks, ensuring you stay ahead of industry trends. High-impact role where your contributions directly influence startup success and scale. Be a part of an amazing work culture and environment where you get to be your own self. Show more Show less

What is Contentstack Contentstack is on a mission to deliver the world&aposs best digital experiences through a fusion of cutting-edge content management, customer data, personalization and AI technology. Iconic brands, such as AirFrance KLM, ASICS, Burberry, Mattel, Mitsubishi and Walmart, depend on the platform to rise above the noise in today&aposs crowded digital markets and gain their competitive edge. Contentstack and its employees are dedicated to the customers and communities they serve. The company is recognized for its unmatched customer care and tradition of giving back globally through the Contentstack Cares program, including proud support of Pledge 1% and Girls Who Code. Learn more at www.contentstack.com. Who Are We At Contentstack we are more than colleagues, we are a tribe. Our vision is to pursue equity among our communities, employees, partners, and customers. We are global-diverse yet close; distributed yet connected. We are dreamers and dreammakers who challenge the status quo. We do the right thing, even when no one is watching. We are curious trendspotters and brave trendsetters. Our mission is to make Contentstack indispensable for organizations to tell their stories and to connect with the people they care about through inspiring, modern experiences. We care deeply about our customers and the communities we serve. #OneTeamOneDream. Chalo, let&aposs go! Roles & Responsibilities The primary purpose of this role is to be part of the R&D Disruptive product team ideating, developing the MVP product developing new products.. Working with emerging technologies Trying out new Technologies and developing prototypes Work with different product and engineering teams for adoption of the emerging tech within the stable products Work across the stack from a code commit to running it in production, with the end goal of delivering the best possible experience for the user Design, develop and test features from inception to rollout Write high quality code that is scalable, testable, maintainable and reliable Collaborate with people across roles to understand the domain and work towards building the right solution Adopt an open mindset for learning new things and working in new roles Continuously improve by working on and providing feedback Requirements Knoweledge of Generative AI (LLM) Experince in integrating with LLM APIs like(function calling, MCP) Experince in working with LLM Agents and creating Agentic AI solution Experince in creating RAG pipeline. experince in Prompt Engineering Ability to learn new skills quickly and apply them to solving tough problems Object-oriented design and development skills Good understanding of the Software Development Life Cycle Knowledge of the following: Html, CSS, Javascript, Node.js Good communication skills Exposure to databases like MongoDB, Redis, and/or any Relational databases is preferred What Really Gets Us Excited About You Working independently on the emerging technologies Curiosity and deep interest in solving problems Project/intern experience in working with software product companies What Do We Offer Interesting Work | We hire curious trendspotters and brave trendsetters. This is NOT your boring, routine, cushy, rest-and-vest corporate job. This is the "challenge yourself" role where you learn something new every day, never stop growing, and have fun while you&aposre doing it. Tribe Vibe | We are more than colleagues, we are a tribe. We have a strict "no a**hole policy" and enforce it diligently. This means we spend time together - with spontaneous office happy hours, organized outings, and community volunteer opportunities. We are a diverse and distributed team, but we like to stay connected. Bragging Rights | We are dreamers and dream makers. Our efforts pay off and we work with the most prestigious brands, from big-name retailers to airlines, to professional sports teams. Your contribution will make an impact with many of the most recognizable names in almost every industry including AirFrance KLM, ASICS, Burberry, Mattel, Mitsubishi, Walmart, and many more! One Team One Dream | This is one of our values, and it shows. We don&apost believe in artificial hierarchies. If you&aposre part of the tribe, you have an opportunity to contribute. Your voice will be heard and you will also receive regular updates about the business and its performance. Which, btw, is through the roof, so it&aposs a great time to be joining To review our Privacy Policy, please click here. Show more Show less

As an AI QA Consultant at Atrium, you will play a pivotal role in ensuring the quality, functionality, and performance of our AI solutions. Your responsibilities will revolve around testing AI features on the Salesforce platform, focusing on validating AI-powered features, agentic workflows, and integrations with Large Language Models (LLMs). This unique position combines traditional Salesforce QA with modern AI testing principles, necessitating a deep understanding of Salesforce best practices, attention to detail, and technical proficiency in testing complex, non-deterministic systems. Your collaboration with AI developers, Salesforce administrators, and business stakeholders will be crucial in delivering robust and reliable AI-driven user experiences. Your key responsibilities will include conducting thorough manual and exploratory testing of AI features on the Salesforce platform. You will be responsible for identifying, documenting, and tracking defects in Jira, distinguishing between standard configuration bugs and nuanced, probabilistic issues inherent in AI model outputs. Ownership of data quality throughout the AI fine-tuning lifecycle will be a significant aspect of your role, ensuring the validation and preparation of high-quality, unbiased datasets essential for building reliable enterprise AI. Additionally, you will be tasked with developing detailed test plans, test cases, and test scripts tailored to evaluate the accuracy, relevance, safety, and performance of LLM responses and AI-driven logic. Collaboration with product owners and AI developers to understand requirements and design comprehensive test strategies for Salesforce solutions incorporating AI components will be essential. You will create scenarios to test for vulnerabilities such as prompt injection, model hallucinations, data grounding issues, and bias in AI outputs. Evaluating the performance, latency, and resource consumption of AI features to meet user experience benchmarks will also be part of your responsibilities. Furthermore, you will facilitate User Acceptance Testing (UAT) for AI-powered features, guiding business users on evaluating and providing feedback on intelligent systems. Staying abreast of the latest advancements in LLMs, prompt engineering techniques, and AI testing methodologies will be crucial, as you champion the adoption of best practices. To excel in this role, you should have a strong foundation with 2-3 years of dedicated QA experience on the Salesforce platform. An understanding of modern AI/NLP concepts, including Retrieval-Augmented Generation (RAG), model fine-tuning, and creating feedback loops for reinforcement learning is essential. Proficiency in Python for writing test scripts, data manipulation, and interacting with AI APIs is required. Hands-on experience with LLM APIs, frameworks like LangChain/LlamaIndex, and various Vector Databases will be beneficial. Knowledge of SQL, NoSQL, and vector databases is also important. Excellent analytical and communication skills, along with experience in thriving in an Agile/Scrum environment, will be key to success in this role. At Atrium, we value diversity in our workforce to align with our growth ambitions and foster inclusion across the business. We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.,

You should have 3 to 10 years of experience in AI development and be located in Coimbatore. Immediate joiners are preferred. A minimum of 2 years of experience in core Gen AI is required. As an AI Developer, your responsibilities will include designing, developing, and fine-tuning Large Language Models (LLMs) for various in-house applications. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Additionally, you will develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Building and managing data pipelines for processing, transforming, and feeding structured/unstructured data into AI models will be part of your role. It is essential to ensure scalability, performance, and security of AI-driven solutions in production environments. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, is expected. You will conduct experiments and evaluations to improve AI system accuracy and efficiency while staying updated with the latest advancements in AI/ML research, open-source models, and industry best practices. You should have strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases such as Pinecone, ChromaDB, Weaviate, OpenSearch, and FAISS, is required. Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks is preferred. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is necessary. Experience in Python web frameworks such as FastAPI, Django, or Flask is expected. You should also have experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes) is essential. Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications is a plus. A strong understanding of vector search, embedding models, and hybrid retrieval techniques is required. Experience with optimizing inference and serving AI models in real-time production systems is beneficial. Experience with multi-modal AI (text, image, audio) and familiarity with privacy-preserving AI techniques and responsible AI frameworks are desirable. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation, is a plus. Skills required for this role include PyTorch, RAG architectures, OpenSearch, Weaviate, Docker, LLM fine-tuning, ChromaDB, Apache Airflow, LoRA, Python, hybrid retrieval techniques, Django, GCP, CrewAI, OpenAI, Hugging Face, Gen AI, Pinecone, FAISS, AWS, AutoGPT, embedding models, Flask, FastAPI, LLM APIs, DeepSpeed, vector search, PEFT, LangChain, Azure, Spark, Kubernetes, AI Gen, TensorFlow, real-time production systems, LangGraph, and Kafka.,

As an AWS Developer at Marlabs Innovations Pvt Ltd, your main responsibility will be to design and implement a secure and scalable API Gateway on AWS. This API Gateway will serve as the integration point between a Salesforce Force.com application and an LLM (Large Language Model) AI endpoint service. You should have hands-on experience in creating serverless architectures, securing APIs, and connecting cloud-native services with third-party applications and AI/ML platforms. Your key responsibilities will include designing and developing a secure API Gateway on AWS to enable seamless communication between Salesforce and an AI endpoint. You will need to implement Lambda functions, IAM roles, and various authentication mechanisms such as OAuth, API Keys, and Cognito. Ensuring secure, low-latency, and scalable message flow between the Force.com backend and external LLM APIs will be crucial. Additionally, you will be responsible for integrating with Salesforce via REST APIs, managing authentication tokens, and optimizing API performance while handling error retries, logging, and monitoring through CloudWatch. Furthermore, you will need to ensure a fault-tolerant architecture with high availability using services like API Gateway, Lambda, S3, DynamoDB, or other relevant AWS offerings. Collaborating with AI teams to consume LLM endpoints from platforms like OpenAI, Anthropic, or custom-hosted models will also be part of your role. Following best practices in DevOps and Infrastructure as Code (IaC) using tools like CloudFormation or Terraform will be expected. To be successful in this role, you should have strong hands-on experience with AWS API Gateway, AWS Lambda, and IAM. Proficiency in Python or Node.js for Lambda development is required, as well as experience integrating with Salesforce REST APIs and authentication workflows. A good understanding of LLM APIs, AI service integration, secure API development practices, event-driven architectures, and serverless frameworks is essential. Experience with CI/CD pipelines, CloudFormation, or Terraform, along with strong troubleshooting and debugging skills in cloud environments, will be beneficial. Preferred qualifications for this position include being an AWS Certified Developer Associate or holding an equivalent certification. Prior experience in integrating Salesforce with external cloud services, knowledge of AI/ML pipelines, REST-based AI model interactions, and familiarity with API monitoring and analytics tools would be advantageous.,

As an AI/ML & GenAI Developer Intern at ArgyleEnigma Tech Labs working on the FinDocGPT project, you will be part of a groundbreaking initiative to make complex financial documents easily understandable for millions of Indians. This internship opportunity offers a stipend ranging from 8,000 to 12,000 INR per month for a duration of 6 months, starting immediately. At FinDocGPT, we are dedicated to leveraging cutting-edge AI/ML and GenAI technologies to provide a transformative solution that bridges the financial literacy gap in India. Our product, FinDocGPT, is India's first AI-powered assistant that decodes intricate financial documents into simple, regional language, covering areas such as health insurance, loans, and mutual fund terms and conditions. Supported by Google for Startups and the Reserve Bank Innovation Hub, we are on a mission to empower individuals by offering financial information in a language they understand. As an AI/ML & Generative AI Developer Intern, you will have the opportunity to gain hands-on experience in deploying GenAI models, NLP pipelines, and ML-based document processing. Your responsibilities will include working on document classification, NER, and summarization using advanced LLMs such as LLaMA, Mistral, Groq, and open-source models. Additionally, you will preprocess, clean, and structure financial documents in various formats like PDFs, scans, and emails. Collaborating with the product and design teams, you will contribute to building smart and user-friendly interfaces. To excel in this role, you should possess a strong understanding of Python, NLP, and basic ML concepts. Familiarity with transformers like BERT, T5, or GPT architectures is essential. Experience, even in an academic setting, with HuggingFace, LangChain, or LLM APIs is preferred. Knowledge of Google Cloud, AWS, or Docker would be a bonus. We are looking for individuals who are eager to learn, experiment quickly, and create a tangible impact. By joining us, you will receive direct mentorship from industry experts with backgrounds in companies such as Morgan Stanley, PIMCO, and Google. You will gain real-world exposure to AI applications tailored for the Indian market and have the opportunity to transition into a full-time role based on your performance. Your work will directly contribute to enhancing financial inclusion in India. To apply for this internship, please send your CV, GitHub/portfolio, and a brief statement explaining why you are interested in this role to info@argyleenigma.com or apply via https://tinyurl.com/hr-aetl with the subject line "Internship Application - FinDocGPT." This internship is based in Gandhinagar, Gujarat, and requires in-person work. The expected start date is 01/08/2025.,

As an experienced AI Architect with 4+ years of experience, your core responsibilities will involve designing and architecting AI pipelines that encompass ingestion, extraction, deduplication, quality checks, reasoning, and visualization using LLM-based technologies. You will be tasked with creating agentic workflows that efficiently coordinate various tools, functions, and data sources through orchestration frameworks. Additionally, your role will require building user-facing agents that can interpret queries, retrieve data, and deliver tailored outputs utilizing RAG technology. Collaborating with product, engineering, and domain experts, you will integrate AI applications into production environments and develop generative interfaces for tasks like report generation, insight synthesis, and stakeholder communications. Furthermore, you will be responsible for defining LLM customization strategies, including fine-tuning, prompt engineering, and retrieval optimization. Your expertise in Prompt Engineering will be crucial, as you will be crafting and refining prompts to guide task-specific LLM behavior. Practical experience with LLM APIs from providers like OpenAI, Anthropic, or similar platforms is essential. Familiarity with RAG, embeddings, and retrieval-augmented generation patterns will be required for creating user-friendly agents. Proficiency in software development using Python, Git, testing, and modern development practices is necessary. Working knowledge of NLP techniques such as entity recognition, text classification, and model adaptation will also be beneficial. Additionally, you should be able to define and track metrics for accuracy, latency, and hallucination in LLM agents and have experience in generative visualization using tools like Vega-Lite, Observable, or custom pipelines. Ideally, you should hold a Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or possess equivalent hands-on experience. You must have at least two years of experience developing production software, with a minimum of one year dedicated to building LLM-driven applications or AI agents. A portfolio, GitHub repository, or case study showcasing AI-enabled solutions in real or simulated environments would be advantageous. Bonus skills that would set you apart include an understanding of LLM fine-tuning, agent orchestration frameworks like CrewAI or LangChain, knowledge of open-source LLMs such as LLaMA, familiarity with AWS and Docker, and hands-on experience with transformer libraries like Hugging Face. This is a full-time position that requires working in person.,

Immediate Hiring for GenAI Developer Contract/Subcorn/C2H Skill - GenAI developer EXP Range - 7 - 10 yrs Location - BGL/HYD/MUM Skills Required Experience in LLM APIs, Prompt engineering and fine tuning, RAG Pipelines, Python, Pyspark, SQL (Primary) Experience in one major cloud provider Snowflake, Databricks, Informatica

You should have 6-10+ years of experience in AI/ML development, including at least 3 years of hands-on experience in Generative AI, RAG frameworks, and Agentic AI systems. As a Generative AI Engineer, you will be responsible for designing, developing, and optimizing RAG pipelines using frameworks such as LangChain, LlamaIndex, or custom-built stacks. You will also implement Agentic AI architectures involving task-based agents, stateful memory, planning-execution workflows, and tool augmentation. Additionally, you will perform model fine-tuning, embedding generation, and evaluation of LLM outputs while incorporating human and automated feedback loops. Building and enforcing guardrails to ensure safe, compliant, and robust model behavior will be a crucial part of your role, including prompt validation, output moderation, and access controls. Collaboration with cross-functional teams to deploy solutions in cloud-native environments such as Azure OpenAI, AWS Bedrock, or Google Vertex AI will also be expected. Furthermore, you will contribute to system observability via dashboards and logging, as well as support post-deployment model monitoring and optimization. To excel in this role, you must have proven production experience with RAG frameworks like LangChain, LlamaIndex, or custom-built solutions. A solid understanding of Agentic AI design patterns, strong expertise in LLM fine-tuning, vector embeddings, evaluation strategies, and feedback integration are essential. Experience with implementing AI guardrails, proficiency in Python, LLM APIs (OpenAI, Anthropic, Cohere, etc.), and vector database integration are also required. Familiarity with CI/CD pipelines, API integrations, and cloud-native deployment patterns is a plus. Preferred qualifications include experience working on AI projects in regulated environments (Banking domain), hands-on experience with cloud AI platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI, knowledge of prompt engineering, RLHF, and LLM observability frameworks, as well as experience building or leveraging internal LLM evaluation harnesses, agent orchestration layers, or compliance dashboards.,

Inviting applications for the role of Principal Consultant -MLOps Engineer! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities . Develop and maintain CI/CD pipelines for AI/GenAI models on AWS using GitHub Actions and CodePipeline. (Not Limited to) . Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) . Any cloud platform- Azure or AWS . Package and deploy AI/GenAI models on (SageMaker, Lambda, API Gateway). . Write Python scripts for automation, deployment, and monitoring. . Engaging in the design, development and maintenance of data pipelines for various AI use cases . Active contribution to key deliverables as part of an agile development team . Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). . Ensure model governance, versioning, and traceability across environments. . Collaborating with others to source, analyse, test and deploy data processes . Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. . Degree/qualification in Computer Science or a related field, or equivalent work experience . Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. . Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills . Experience with Docker-based deployments. . Exposure to model monitoring tools (Evidently, CloudWatch). . Familiarity with RAG stacks or fine-tuning LLMs. . Understanding of GitOps practices. . Knowledge of governance and compliance policies, standards, and procedures

You will be joining the engineering team at STAND 8 as a Senior AI Engineer / Data Engineer where you will play a key role in developing cutting-edge AI-powered business solutions. Your primary focus will be designing and optimizing AI systems that utilize advanced large language models, real-time AI interactions, and state-of-the-art retrieval architectures. Your contributions will directly impact products that are revolutionizing various business operations, especially in areas such as recruitment, data extraction, and decision-making processes. As a Senior AI Engineer / Data Engineer at STAND 8, your responsibilities will include designing, building, and enhancing AI-powered systems that incorporate multi-modal architectures encompassing text, voice, and visual elements. You will also be tasked with integrating and deploying large language model (LLM) APIs from providers like OpenAI, Anthropic, and AWS Bedrock, as well as constructing and managing Retrieval-Augmented Generation (RAG) systems with hybrid search capabilities, re-ranking functionalities, and knowledge graphs. Additionally, you will develop real-time AI features using streaming analytics and voice interaction tools, build APIs and pipelines to support AI workflows, process unstructured documents with layout and semantic understanding, implement predictive models, and deploy scalable solutions using various AWS services. Your role will also involve utilizing Docker for containerization, managing CI/CD workflows, version control through Git, debugging, monitoring, and optimizing performance for large-scale data pipelines, and collaborating with cross-functional teams consisting of product, data, and engineering professionals. To qualify for this role, you should possess at least 5 years of experience in AI/ML or data engineering with Python in production environments. Hands-on experience with LLM APIs and frameworks such as OpenAI, Anthropic, Bedrock, or LangChain is essential, along with expertise in vector databases like PGVector, Weaviate, FAISS, or Pinecone, a strong grasp of NLP, document extraction, and text processing, proficiency in AWS cloud services, experience with FastAPI or similar frameworks, familiarity with embedding models, prompt engineering, and RAG systems, knowledge of asynchronous programming, Docker, Git workflows, CI/CD pipelines, and testing best practices. Preferred qualifications include a background in HRTech or ATS integrations, knowledge of knowledge graphs for semantic relationships, experience with real-time AI systems and voice AI tools, advanced Python development skills, large-scale data processing experience, event-driven architecture knowledge using AWS services, and hands-on experience with fine-tuning, evaluating, and deploying foundation models.,

STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India. We are looking for a Senior AI Engineer / Data Engineer to be a part of our engineering team and contribute to building the future of AI-powered business solutions. In this role, you will be involved in developing intelligent systems that make use of advanced large language models (LLMs), real-time AI interactions, and cutting-edge retrieval architectures. Your efforts will have a direct impact on products that are revolutionizing business operations, particularly in the areas of recruitment, data extraction, and intelligent decision-making. This position offers an exciting opportunity for individuals who excel in constructing production-grade AI systems and are adept at working across the full spectrum of modern AI technologies. Responsibilities - Design, construct, and enhance AI-powered systems utilizing multi-modal architectures encompassing text, voice, and visual elements. - Incorporate and deploy LLM APIs sourced from providers like OpenAI, Anthropic, and AWS Bedrock. - Develop and manage RAG (Retrieval-Augmented Generation) systems featuring hybrid search, re-ranking, and knowledge graphs. - Create real-time AI functionalities through the utilization of streaming analytics and voice interaction tools such as ElevenLabs. - Establish APIs and pipelines using FastAPI or similar frameworks to facilitate AI workflows. - Process and evaluate unstructured documents with an understanding of layout and semantics. - Implement predictive models that drive intelligent business recommendations. - Deploy and sustain scalable solutions leveraging AWS services like EC2, S3, RDS, Lambda, Bedrock, among others. - Utilize Docker for containerization and oversee CI/CD workflows and version control via Git. - Debug, monitor, and optimize performance for large-scale data pipelines. - Collaborate seamlessly with product, data, and engineering teams across different functions. Qualifications - Possess 5+ years of experience in AI/ML or data engineering utilizing Python in production environments. - Hands-on familiarity with LLM APIs and frameworks such as OpenAI, Anthropic, Bedrock, or LangChain. - Previous experience in deploying vector databases like PGVector, Weaviate, FAISS, or Pinecone in production settings. - Solid grasp of NLP, document extraction, and text processing. - Proficiency in AWS cloud services including Bedrock, EC2, S3, Lambda, and monitoring tools. - Experience with FastAPI or similar frameworks for constructing AI/ML APIs. - Knowledge of embedding models, prompt engineering, and RAG systems. - Proficiency in asynchronous programming for high-throughput pipelines. - Proficiency in Docker, Git workflows, CI/CD pipelines, and adherence to testing best practices. Preferred - Background in HRTech or ATS integrations (e.g., Greenhouse, Workday, Bullhorn). - Experience working with knowledge graphs (e.g., Neo4j) for semantic relationships. - Exposure to real-time AI systems (e.g., WebRTC, OpenAI Realtime API) and voice AI tools (e.g., ElevenLabs). - Advanced Python development skills employing design patterns and clean architecture. - Experience in large-scale data processing (1-2M+ records) with cost optimization techniques for LLMs. - Proficiency in event-driven architecture utilizing AWS SQS, SNS, or EventBridge. - Hands-on experience with fine-tuning, evaluating, and deploying foundation models.,

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant - MLOps Engineer! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities Develop and maintain CI/CD pipelines for AI/ GenAI models on AWS using GitHub Actions and CodePipeline . (Not Limited to) Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) Any cloud platform - Azure or AWS Package and deploy AI/ GenAI models on (SageMaker, Lambda, API Gateway). Write Python scripts for automation, deployment, and monitoring. Engaging in the design, development and maintenance of data pipelines for various AI use cases Active contribution to key deliverables as part of an agile development team Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). Ensure model governance, versioning, and traceability across environments. Collaborating with others to source, analyse , test and deploy data processes Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. Degree/qualification in Computer Science or a related field, or equivalent work experience Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/ GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills Experience with Docker-based deployments. Exposure to model monitoring tools (Evidently, CloudWatch). Familiarity with RAG stacks or fine-tuning LLMs. Understanding of GitOps practices. Knowledge of governance and compliance policies, standards, and procedures Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions. You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems. Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads. Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs. Build CI/CD pipelines with integrated prompt regression testing and version control. Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows. Monitor system performance using tools like Langfuse or Prometheus. Data and Document Ingestion Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data. Apply preprocessing pipelines for text, images, and code. Ensure data integrity, format consistency, and security across sources. AI Service Integration Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.). Build internal APIs for smooth backend-AI communication. Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets. Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy. Retrieval-Augmented Generation (RAG) Pipelines Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API). Design custom retrieval strategies for multi-modal or multi-source documents. Apply post-retrieval ranking using DPO or feedback-based techniques. Improve contextual relevance through re-ranking, chunk merging, and scoring logic. LLM Integration and Optimization Manage prompt engineering, model interaction, and tuning workflows. Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design. Optimize generation using temperature tuning, token limits, and speculative decoding. Integrate observability and cost-monitoring into LLM workflows. Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications. Implement monitoring, logging, and performance tracing. Build RBAC (Role-Based Access Control) and multi-tenant personalization. Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production. Required Skills and Qualifications Education Bachelors or Masters in Computer Science, Artificial Intelligence, Machine Learning, or related field. Experience 5+ years of experience in AI/ML engineering with end-to-end pipeline development. Hands-on experience building and deploying LLM/RAG systems in production. Strong experience with public cloud platforms (AWS, Azure, or GCP). Technical Skills Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch. Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph. Experience with RESTful API development and version control using Git. Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval. Familiarity with Docker, Kubernetes, and scalable microservice design. Experience with observability tools like Prometheus, Grafana, or Langfuse. Generative AI Specific Skills Knowledge of LLMs, VAEs, Diffusion Models, GANs. Experience building structured + unstructured RAG pipelines. Prompt engineering with safety controls, schema enforcement, and hallucination mitigation. Experience with prompt testing, caching strategies, output filtering, and fallback logic. Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods. Soft Skills Strong analytical, problem-solving, and debugging skills. Excellent collaboration with cross-functional teams: product, QA, and DevOps. Ability to work in fast-paced, agile environments and deliver production-grade solutions. Clear communication and strong documentation practices. Preferred Qualifications Experience with OCR, document parsing, and layout-aware chunking. Hands-on with MLOps and LLMOps tools for Generative AI. Contributions to open-source GenAI or AI infrastructure projects. Knowledge of GenAI governance, ethical deployment, and usage controls. Experience with hallucination suppression frameworks like Guardrails.ai, Rebuff, or Constitutional AI. Shift Time: 2:30 PM to 11:30 PM IST Location-Remote,Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Inviting applications for the role of Senior Principal Consultant - ML Engineers! In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments. Responsibilities . Develop and maintain CI/CD pipelines for AI/GenAI models on AWS using GitHub Actions and CodePipeline. (Not Limited to) . Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc) . Any cloud platform- Azure or AWS . Package and deploy AI/GenAI models on (SageMaker, Lambda, API Gateway). . Write Python scripts for automation, deployment, and monitoring. . Engaging in the design, development and maintenance of data pipelines for various AI use cases . Active contribution to key deliverables as part of an agile development team . Set up model monitoring, logging, and alerting (e.g., drift, latency, failures). . Ensure model governance, versioning, and traceability across environments. . Collaborating with others to source, analyse, test and deploy data processes . Experience in GenAI project Qualifications we seek in you! Minimum Qualifications experience with MLOps practices. . Degree/qualification in Computer Science or a related field, or equivalent work experience . Experience developing, testing, and deploying data pipelines Strong Python programming skills. Hands-on experience in deploying 2 - 3 AI/GenAI models in AWS. Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases. . Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills . Experience with Docker-based deployments. . Exposure to model monitoring tools (Evidently, CloudWatch). . Familiarity with RAG stacks or fine-tuning LLMs. . Understanding of GitOps practices. . Knowledge of governance and compliance policies, standards, and procedures . . . . .

About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions. You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems. Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads. Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs. Build CI/CD pipelines with integrated prompt regression testing and version control. Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows. Monitor system performance using tools like Langfuse or Prometheus. Data and Document Ingestion Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data. Apply preprocessing pipelines for text, images, and code. Ensure data integrity, format consistency, and security across sources. AI Service Integration Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.). Build internal APIs for smooth backend-AI communication. Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets. Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy. Retrieval-Augmented Generation (RAG) Pipelines Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API). Design custom retrieval strategies for multi-modal or multi-source documents. Apply post-retrieval ranking using DPO or feedback-based techniques. Improve contextual relevance through re-ranking, chunk merging, and scoring logic. LLM Integration and Optimization Manage prompt engineering, model interaction, and tuning workflows. Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design. Optimize generation using temperature tuning, token limits, and speculative decoding. Integrate observability and cost-monitoring into LLM workflows. Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications. Implement monitoring, logging, and performance tracing. Build RBAC (Role-Based Access Control) and multi-tenant personalization. Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production. Required Skills and Qualifications Education Bachelors or Masters in Computer Science, Artificial Intelligence, Machine Learning, or related field. Experience 5+ years of experience in AI/ML engineering with end-to-end pipeline development. Hands-on experience building and deploying LLM/RAG systems in production. Strong experience with public cloud platforms (AWS, Azure, or GCP). Technical Skills Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch. Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph. Experience with RESTful API development and version control using Git. Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval. Familiarity with Docker, Kubernetes, and scalable microservice design. Experience with observability tools like Prometheus, Grafana, or Langfuse. Generative AI Specific Skills Knowledge of LLMs, VAEs, Diffusion Models, GANs. Experience building structured + unstructured RAG pipelines. Prompt engineering with safety controls, schema enforcement, and hallucination mitigation. Experience with prompt testing, caching strategies, output filtering, and fallback logic. Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods. Soft Skills Strong analytical, problem-solving, and debugging skills. Excellent collaboration with cross-functional teams: product, QA, and DevOps. Ability to work in fast-paced, agile environments and deliver production-grade solutions. Clear communication and strong documentation practices. Preferred Qualifications Experience with OCR, document parsing, and layout-aware chunking. Hands-on with MLOps and LLMOps tools for Generative AI. Contributions to open-source GenAI or AI infrastructure projects. Knowledge of GenAI governance, ethical deployment, and usage controls. Experience with hallucination suppression frameworks like Guardrails.ai, Rebuff, or Constitutional AI. Experience and Shift Shift Time: 2:30 PM to 11:30 PM IST Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

Role & responsibilities : Requirements: Strong expertise in NLP, text summarization, semantic search, and LLM APIs. Practical experience with Amazon Bedrock, OpenAI, or Hugging Face transformers. Familiar with prompt tuning and few-shot learning. Python (pandas, langchain, boto3, NumPy, etc.) Experience working with unstructured audio-to-text data (e.g., call transcripts). Key Responsibilities: Design and Development: Design, develop, and deploy LLM-based solutions for text summarization, semantic search, and other NLP tasks LLM APIs: Integrate LLM APIs from Amazon Bedrock, OpenAI, or Hugging Face transformers into existing applications Prompt Tuning and Few-Shot Learning: Implement prompt tuning and few-shot learning techniques to improve LLM performance Unstructured Audio-to-Text Data: Work with unstructured audio-to-text data, such as call transcripts, to develop accurate and efficient NLP models Python Programming: Utilize Python libraries like pandas, LangChain, boto3, and NumPy for data processing and model development Preferred candidate profile : We're seeking a highly skilled NLP Engineer with expertise in Large Language Models (LLMs) and text summarization to join our team. The ideal candidate will have hands-on experience with Amazon Bedrock, OpenAI, or Hugging Face transformers and a strong background in Python programming. This role involves working with unstructured audio-to-text data, such as call transcripts, and developing innovative solutions using LLMs.

The JD for AI/Ml programmer is given below: Key Responsibilities: Design, develop, and deploy Generative AI models using state-of-the-art architectures (e.g., Transformers, Diffusion models). Build and fine-tune LLM-powered agents capable of multi-step reasoning, task planning, and tool use. Work with frameworks like LangChain, AutoGPT, BabyAGI, CrewAI , or similar agent orchestration tools. Integrate models with REST APIs, vector databases (e.g., Pinecone, FAISS, Chroma), and external systems. Optimize inference pipelines for performance, latency, and scalability. Collaborate with product managers and data scientists to prototype and productionize AI features. Stay updated on recent advancements in Generative AI and autonomous agents. Required Qualifications: 34 years of hands-on experience in Machine Learning / Deep Learning , with at least 1–2 years in Generative AI and/or AI Agents . Proficiency in Python and ML libraries such as PyTorch , TensorFlow , Transformers (Hugging Face) . Experience with LLM APIs (OpenAI, Claude, Mistral, etc.) and building LLM-based applications. Solid understanding of prompt engineering , fine-tuning , RAG (Retrieval-Augmented Generation) , and multi-modal learning . Familiarity with agent orchestration frameworks and LLM tool chaining . Strong problem-solving and communication skills. Preferred Qualifications: Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Weights & Biases). Knowledge of Reinforcement Learning or Meta-learning for agent training. Experience contributing to open-source projects or published papers in the field of AI.