18 Aws Bedrock Jobs

Key Responsibilities: Design, develop, and implement AI-driven chatbots and IVAs to streamline customer interactions. Work on conversational AI platforms to create a seamless customer experience, with a focus on natural language processing (NLP), intent recognition, and sentiment analysis. Collaborate with cross-functional teams, including product managers and customer support, to translate business requirements into technical solutions. Build, train, and fine-tune machine learning models to enhance IVA capabilities and ensure high accuracy in responses. Continuously optimize models based on user feedback and data-driven insights to improve performance. Integrate IVA/chat solutions with internal systems such as CRM and backend databases. Ensure scalability, robustness, and security of IVA/chat solutions in compliance with industry standards. Participate in code reviews, testing, and deployment of AI solutions to ensure high quality and reliability. Required Skills and Qualifications: Bachelors or master’s degree in computer science, Data Science, AI/ML, or a related field. 3+ years of experience in developing IVA/chatbots, conversational AI, or similar AI-driven systems using AWS services Expert in using Amazon Lex, Amazon Polly, AWS lambda, AWS connect AWS Bedrock experience with Sage maker will have added advantage Solid understanding of API integration and experience working with RESTful services. Strong problem-solving skills, attention to detail, and ability to work independently and in a team. Excellent communication skills in English, both written and verbal. Preferred Qualifications: Experience in financial services or fintech projects. Knowledge of data security best practices and compliance requirements in the financial sector.

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-3-9YRS In Gen AI AWS PKG Upto-25LPA Loc- Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-4-12YRS In Gen AI AWS PKG Upto-25LPA Loc-Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Role Overview We are seeking a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate has hands-on experience developing, fine-tuning, and deploying LLMs, alongside a deep understanding of the machine learning lifecycle. This role involves building scalable AI solutions, collaborating with cross-functional teams, and contributing to cutting-edge AI initiatives. Key Responsibilities Model Development & Optimization: Develop, fine-tune, and deploy LLMs like OpenAI's GPT, Anthropic's Claude, Googles Gemini, or AWS Bedrock. Customize pre-trained models for specific use cases, ensuring high performance and scalability. Machine Learning Pipeline Design: Build and maintain end-to-end ML pipelines, from data preprocessing to model deployment. Optimize training workflows for efficiency and accuracy. Integration & Deployment: Work closely with software engineering teams to integrate ML solutions into production environments. Ensure APIs and solutions are scalable and robust. Experimentation & Research: Experiment with new architectures, frameworks, and approaches to improve model performance. Stay updated with advancements in LLMs and generative AI technologies. Collaboration: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align ML solutions with business goals. Provide mentorship to junior team members as needed. Required Qualifications Experience: At least 5 years of professional experience in machine learning or AI development. Proven experience with LLMs and generative AI technologies. Technical Skills: Proficiency in Python (required) and basic knowledge of Java is needed Hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock. Familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face. Strong understanding of data structures, algorithms, and distributed systems. Cloud Expertise: Experience with AWS, GCP, or Azure, including services relevant to ML workloads (e.g., AWS SageMaker, Bedrock). Data Engineering: Proficiency in handling large-scale datasets and implementing data pipelines. Experience with ETL tools and platforms for efficient data preprocessing. Problem Solving: Strong analytical and problem-solving skills, with the ability to debug and resolve issues quickly. Preferred Qualifications Experience with multi-modal models and generative AI for images, text, or other modalities. Understanding of ML Ops principles and tools (e.g., MLflow, Kubeflow). Familiarity with reinforcement learning and its applications in AI. Knowledge of distributed training techniques and tools like Horovod or Ray. Advanced degree (Masters or Ph.D.) in Computer Science, Machine Learning, or a related field.

Job Overview: We are seeking an experienced and passionate Technical Manager/Lead to spearhead our cutting-edge AI initiatives including Phoenix Ask , Phoenix Report Writer , and upcoming AI-powered features. This role will lead a team of 5 Senior Developers focused on developing, deploying, and maintaining advanced AI capabilities using state-of-the-art models and technologies. Key Responsibilities: Lead the design, development, and deployment of scalable AI features and tools. Manage and mentor a team of senior AI developers. Collaborate with cross-functional teams (Product, UX, DevOps) to deliver commercial-ready AI features. Architect AI-driven solutions using modern frameworks and cloud platforms. Ensure best practices in model selection, prompt engineering, fine-tuning, and evaluation. Deploy AI applications using Azure Foundry , AWS Bedrock , and similar platforms. Oversee integration of models like GPT-4o , GPT-o3 , Claude , and LLaMA into business products. Maintain robust documentation and ensure product scalability and performance. Required Skills & Experience: 5+ years of experience in AI/ML development with at least 2 years in a leadership role . Strong expertise in Langchain , Pydantic , and FastAPI . Experience working with MCP (Modular Code Platforms or Microsoft Cloud Platform clarify as needed). Proven hands-on experience with deploying models like GPT-4o, GPT-o3, Claude, LLaMA . Solid understanding of AI model training , fine-tuning , and industry-standard tools . Strong deployment experience on Azure Foundry and AWS Bedrock or equivalent cloud services. Ability to manage sprints, code reviews, and project delivery timelines. Preferred Qualifications: Master's/Bachelors degree in Computer Science, Artificial Intelligence, or related field. Experience in integrating AI with enterprise systems. Prior work on generative AI or natural language applications.

Summary Bitkraft Technologies LLP is looking for a Senior DevOps Engineer to join our software engineering team. The DevOps engineer will be responsible for implementing cutting-edge technology and solving real-life challenges in a variety of client environments using VI Editor & YAML Editor. If you love solving problems, are a team player, and want to work in a fast-paced environment with core technical and business challenges, we would like to meet you. Key Skills Azure, GitHub Actions, Kubernetes, Infrastructure, Terraform AWS Bedrock (part of Generative AI), Amazon Q, Generative AI, Quicksight Pro Certification in Cloud Technologies Key Responsibilities DevOps Frameworks : Implement and work with newer frameworks in the DevOps landscape, ensuring up-to-date practices and methodologies. Infrastructure as Code : Develop and maintain infrastructure as code solutions, enabling scalable and manageable infrastructure deployment. Microservice Architecture Management : Manage and optimize microservices architectures, ensuring high availability and efficient operation of services. GitHub Actions : Utilize mandatory GitHub actions for automating workflows, including CI/CD pipelines and infrastructure deployment. Infrastructure Automation : Focus on automating the building and maintenance of infrastructure, both in cloud environments and on-premises setups. Cloud and On-Premise Solutions : Work across both cloud and on-premise environments, demonstrating flexibility and adaptability in various infrastructural contexts. Kubernetes Expertise : Manage and optimize container orchestration using Kubernetes, ensuring efficient deployment, scaling, and management of applications. Repository Management : Experience working with both Monorepo and polyrepo setups, understanding the nuances and best practices of each. Tech Stack Proficiency : Proficient in Java and able to leverage this in a DevOps context to improve systems and processes. AWS & Generative AI : Work with AWS Bedrock, Amazon Q, and other Generative AI tools to optimize cloud and automation processes. Visualization & Monitoring : Utilize AWS Quicksight for data visualization and monitoring infrastructure performance. Qualifications Proven experience as a DevOps Engineer, with a focus on modern DevOps practices and tools. Strong knowledge of infrastructure as code and experience in managing microservice architectures. Proficient in GitHub Actions and experienced in automating infrastructure development. Experience working with both cloud and on-premises environments. Demonstrable skills in Kubernetes and familiarity with Monorepo and polyrepo setups Technical proficiency in Java. Experience with AWS Bedrock, Amazon Q, and Generative AI tools. Strong expertise in AWS Quicksight for infrastructure monitoring. Cloud Pro Certification is highly preferred. Excellent problem-solving skills and the ability to work independently or as part of a team. Strong communication skills and the ability to collaborate effectively with cross-functional teams. Experience 5+ years

Mandatory Skills Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have skills - Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

JD is below: Design, develop, and deploy generative AI based applications using AWS Bedrock. Proficiency in prompt engineering and RAG pipeline Experience in building Agentic Generative AI applications Fine-tune and optimize foundation models from AWS Bedrock for various use cases. Integrate generative AI capabilities into enterprise applications and workflows. Collaborate with cross-functional teams, including data scientists, ML engineers, and software developers, to implement AI-powered solutions. Utilize AWS services (S3, Lambda, SageMaker, etc.) to build scalable AI solutions. Develop APIs and interfaces to enable seamless interaction with AI models. Monitor model performance, conduct A/B testing, and enhance AI-driven products. Ensure compliance with AI ethics, governance, and security best practices. Stay up-to-date with advancements in generative AI and AWS cloud technologies. Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, AI, Machine Learning, or a related field. 3+ years of experience in AI/ML development, with a focus on generative AI. Hands-on experience with AWS Bedrock and foundation models. Proficiency in Python and ML frameworks. Experience with AWS services such as SageMaker, Lambda, API Gateway, DynamoDB, and S3. Experience with prompt engineering, model fine-tuning, and inference optimization. Familiarity with MLOps practices and CI/CD pipelines for AI deployment. Ability to work with large-scale datasets and optimize AI models for performance. Excellent problem-solving skills and ability to work in an agile environment. Preferred Qualifications: AWS Certified Machine Learning – Specialty or equivalent certification. Experience in LLMOps and model lifecycle management. Knowledge of multi-modal AI models (text, image, video generation). Hands-on experience with other cloud AI platforms (Google Vertex AI, Azure OpenAI). Strong understanding of ethical AI principles and bias mitigation techniques.

3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks Strong understanding of ML algorithms, probability and optimization techniques 6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning Ability to write scalable, production-ready ML code and optimized model inference Experience with developing ML pipelines for text classification, summarization and chat agents Prior experience with SQL and noSQL databases, and Snowflake/Databricks

Roles and Responsibilities: Architecture & Infrastructure Design Architect scalable, resilient, and secure AI/ML infrastructure on AWS using services like EC2, SageMaker, Bedrock, VPC, RDS, DynamoDB, CloudWatch . Develop Infrastructure as Code (IaC) using Terraform , and automate deployments with CI/CD pipelines . Optimize cost and performance of cloud resources used for AI workloads. AI Project Leadership Translate business objectives into actionable AI strategies and solutions. Oversee the entire AI lifecycle from data ingestion, model training, and evaluation to deployment and monitoring. Drive roadmap planning, delivery timelines, and project success metrics. Model Development & Deployment Lead selection and development of AI/ML models, particularly for NLP, GenAI, and AIOps use cases . Implement frameworks for bias detection, explainability , and responsible AI . Enhance model performance through tuning and efficient resource utilization. Security & Compliance Ensure data privacy, security best practices, and compliance with IAM policies, encryption standards , and regulatory frameworks. Perform regular audits and vulnerability assessments to ensure system integrity. Team Leadership & Collaboration Lead and mentor a team of cloud engineers, ML practitioners, software developers, and data analysts. Promote cross-functional collaboration with business and technical stakeholders. Conduct technical reviews and ensure delivery of production-grade solutions. Monitoring & Maintenance Establish robust model monitoring , alerting , and feedback loops to detect drift and maintain model reliability. Ensure ongoing optimization of infrastructure and ML pipelines. Must-Have Skills: 10+ years of experience in IT with 4+ years in AI/ML leadership roles. Strong hands-on experience in AWS services : EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, CloudWatch. Expertise in Python for ML development and automation. Solid understanding of Terraform, Docker, Git , and CI/CD pipelines . Proven track record in delivering AI/ML projects into production environments . Deep understanding of MLOps, model versioning, monitoring , and retraining pipelines . Experience in implementing Responsible AI practices – including fairness, explainability, and bias mitigation. Knowledge of cloud security best practices and IAM role configuration. Excellent leadership, communication, and stakeholder management skills. Good-to-Have Skills: AWS Certifications such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect. Familiarity with data privacy laws and frameworks (GDPR, HIPAA). Experience with AI governance and ethical AI frameworks. Expertise in cost optimization and performance tuning for AI on the cloud. Exposure to LangChain , LLMs , Kubeflow , or GCP-based AI services .

Job Description: Core Skills 3+ years of hands-on experience in AI development, with a strong focus on Traditional AI , Generative AI , and Agent-based AI . Strong proficiency in Python , along with experience using AI libraries and frameworks like TensorFlow , PyTorch , Keras , Hugging Face , and others. Experience with Natural Language Processing (NLP) , Reinforcement Learning (RL) , Computer Vision , and Deep Learning . Solid understanding of AI algorithms , model training , data preprocessing , and evaluation metrics . Experience in working with cloud platforms such as AWS, Azure, or Google Cloud for deploying and scaling AI systems. Familiarity with Generative AI models (like GPT, DALL•E, etc.) and Agent-based systems (autonomous agents, bots, recommendation engines, etc.). Preferred Skills Experience with Generative AI technologies and creative AI solutions for content generation, such as text, images, or videos. Knowledge of AI ethics , bias mitigation , and explainability techniques in AI systems. Hands-on experience in Reinforcement Learning or Multi-Agent Systems . Understanding of DevOps principles and CI/CD pipelines for AI systems deployment. Experience with Data Engineering and working with large datasets. Soft Skills Strong problem-solving and analytical skills. Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders. Ability to lead a team, mentor junior developers, and foster collaboration across departments. Passionate about AI technology and continuous learning.

Technical Skills: Responsible for design and implementation of secure and scalable infrastructure in AWS/Azure cloud. Build and maintain CI/CD pipeline across AWS cloud platform for Data science projects. Own and automate the infrastructure provisioning, demand forecasting and capacity planning. Understanding of GPU VS CPU compute, optimizing model performance as per target environment. Build tools and automation to improve systems availability, reliability, performance, monitoring, and scalability. Model monitoring using cloud monitoring services (AWS cloud watch) Monitoring system, application health, security controls and cost Envision, implement and rollout best MLOps tools and automation. Create ETL pipeline for AI models. Data analytics dashboard, creation, and automation of analytics reporting Ability to deploy AI models built on R, Python etc. Implementation of Model drift detection solution Good understanding of AI model packaging and creating deployable packages on AWS/Azure Cloud Hosting of AI services and their scalabilities on AWS/Azure AI cloud services Hands-on experience working with generative AI services AWS Bedrock, Open AI ChatGPT, Google Bard Additional Requirement: Minimum 3 years of experience with AWS/Azure Experience with current industry standard DevOps tools and practices. Java & Python - Able to demonstrate advanced programming ability in more than one common programming language and scripting languages. Good understanding of data analytics. Handson experience with Quick sight, Power BI etc. Experience with monitoring tools and services such as AWS cloud watch. Experience migrating workloads from on-premises to AWS/Azure. Hands-on experience in Docker, Kubernetes, Terraform and Cloud formation. Excellent experience with source code management tools (git) Strive for Continuous Improvement and build continuous integration, continuous development, and constant deployment pipeline. Excellent Troubleshooting skills Always ready to learn more and adopt new cutting-edge technology with right value proposition. Experience automating routine task. Good to have following certifications: AWS Solution Architect Associate Azure Administrator Associate

3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks Strong understanding of ML algorithms, probability and optimization techniques 6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning Ability to write scalable, production-ready ML code and optimized model inference Experience with developing ML pipelines for text classification, summarization and chat agents Prior experience with SQL and noSQL databases, and Snowflake/Databricks

Position Title: Specialist- Data Science Business Title: Engineer II- Data Science We are seeking a highly motivated and enthusiastic Senior Data Scientist with over 8 years of experience to join our dynamic team. The ideal candidate will have a strong background in AI/ML analytics and a passion for leveraging data to drive business insights and innovation. Key Responsibilities: Develop and implement machine learning models and algorithms. Work closely with project stakeholders to understand requirements and translate them into deliverables. Utilize statistical and machine learning techniques to analyze and interpret complex data sets. Stay updated with the latest advancements in AI/ML technologies and methodologies. Collaborate with cross-functional teams to support various AI/ML initiatives. Qualifications: Bachelors degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. Strong understanding of machine learning, deep learning and Generative AI concepts. Preferred Skills: Experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Computer vision(yolo ), Deep Learning stack, NLP using python Strong knowledge and experience in Generative AI/ LLM based development. Strong experience working with key LLM models APIs (e.g. AWS Bedrock OR Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain OR LlamaIndex OR RAG ) Experience with cloud infrastructure for AI/Generative AI/ML on AWS, Azure. Expertise in building enterprise grade, secure data ingestion pipelines (ETL Gluejob, Quicksight) for unstructured data including indexing, search, and advance retrieval patterns. Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. Proficiency in generating and working with text embeddings with understanding of embedding spaces and their applications in semantic search and information. retrieval. Experience with RAG concepts and fundamentals ( VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. Knowledge of training and fine-tuning Foundation Models (Athropic, Claud, Mistral, etc.), including multimodal inputs and outputs. Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and frameworks. (e.g., pandas, NumPy, scikit-learn), Glue crawler, ETL Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight). Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). Experience with version control systems (e.g., Git, CodeCommit). Good to have Skills Knowledge and Experience in building knowledge graphs in production. Understanding of multi-agent systems and their applications in complex problem-solving scenarios. ** Title/Designation of role are as per Global Team Job profiling. Local Titles are adjusted for understanding of regional candidates applying for job in India. Designations are dependent on years of relevant work experience and performance during interviews.

Need Immediate joiners AWS Bedrock, AI ML Engineer Requirements Verified Experience - 6 - 10 years Need strong AWS AI/ML engineers with expertise in Sage Maker, Lambda, ECS, API Gateway, LangChain, and Vector Databases LLM experience mandatory Strong AWS Experience must have 1 to 2 years hands on in AWS bedrock must have - Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn). - Experience with NLP techniques and libraries (spaCy, Hugging Face Transformers). - Knowledge of cloud-based AI platforms (AWS SageMaker, Google AI). Please inform candidates that it's a long term project for one of our sister company ATBZStrong Hands on AWS, AWS Bedrock(1-2 years), AI/ML, LLM is must have, no levy in the skills . CTC _ open for the right candidate Work mode_ Flexible Best Regards, Uma SW +91 98 22 780 197 uma@starlighthr.com I https://starlighthr.com/

Senior AI/ML Engineer will primarily be responsible to design, develop, and optimize autonomous AI agents that interact with systems, users, and APIs to perform complex tasks. S/he will work at the intersection of LLMs, agentic frameworks, and cloud architectures, developing self-improving AI workflows for automation, coding, and decision-making. Responsibilities Design, build, and deploy AI agents using LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks Integrate large language models (LLMs) (GPT-4,o1, Claude, Llama, Mistral etc.,) into multi-agent systems Develop multi-agent orchestration pipelines, enabling collaboration between AI agents for complex task execution Knowledge of vector databases and embeddings for retrieval-augmented AI (RAG) Implement retrieval-augmented generation (RAG) with vector databases like Milvus, Pinecone, Azure AI Search (with Vector Indexing) Optimize AI workflows using Reinforcement Learning (RLHF) and function calling for improved reasoning and automation Integrate AI agents with APIs, DevOps tools and existing workflows Ensure observability, debugging, and monitoring of AI agent behavior through logging frameworks Implement memory persistence for long-term agent interactions using graph-based memory or event stores Collaborate with cross-functional teams to embed AI agents into DevOps, automation, and software development processes Implement various prompt techniques, including zero-shot, few-shot, chain-of-thought (CoT), and fine-tuning for optimized LLM performance Qualifications B. Tech/B.E. or masters degree in computer science, data science, or a related field 8+ years of strong python programming experience with AI/ML frameworks such as TensorFlow, PyTorch Experience in building self-improving AI agents for software development (e.g., SWE-bots, or self-improving code generation agents) Strong algorithmic thinking, problem-solving skills, and ability to debug AI-driven workflows Knowledge of NLP, semantic search, embeddings, and agent memory management Ability to work with knowledge graphs and symbolic reasoning techniques Familiarity with cloud AI services (Azure AI, AWS Bedrock, Google Vertex AI) and deploying AI agents in Containerized environments like Docker, Kubernetes, AKS or Similar Understanding of LLM Ops, including prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and function calling

We are seeking a highly skilled and experienced Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have a robust development background in any programming stack, including but not limited to Java, .Net, Python, or Node.js. This role requires hands-on experience with AI/ML, preferably using cloud platforms such as AWS Bedrock, Google Vertex AI, or Azure AI. A solid understanding of Generative AI and the ability to manage multiple projects end-to-end is essential. AI/ML Engineers code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR).Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages. Primary Responsibilities: Technical Expertise: Utilize solid development skills in programming languages such as Java, .Net, Python, or Node.js Oversee the design, development, and deployment of AI/ML models and solutions Optimize and fine-tune AI/ML models for performance and scalability Ensure best practices in coding, testing, and deployment Own technology decisions and solutions for business problems Stay updated with the latest advancements in AI/ML techniques and tools, and identify opportunities to apply them to enhance existing solutions Project Delivery: Work on the full life cycle of AI/ML projects, including data preparation, model development, tuning, and deployment Manage multiple AI/ML projects simultaneously, ensuring timely delivery and quality Collaborate with cross-functional teams to define project requirements and deliverables Monitor quality of project and adjust plans as necessary to meet objectives Stakeholder Engagement: Communicate effectively with stakeholders to understand their needs and provide technical insights Present project updates, results, and recommendations to senior management Innovation and Research: Conduct research to identify new opportunities for AI/ML applications Encourage a culture of continuous learning and improvement within the team Analyzes and investigates Provides explanations and interpretations within area of expertise Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or a related field Experience: 10+ years of experience in software development 3+ years of experience delivering solutions with a focus on AI/ML Hands-on experience in delivering production-grade AI/ML projects Proven experience in leading and managing technical teams Experience with deploying AI/ML models in production environments using cloud platforms like AWS, Azure, or GCP Solid background in programming languages such as Java, .Net, Python, or Node.js Skills: Experience with cloud platforms AI Stacks like AWS Bedrock, Azure AI, GCP Vertex AI is a plus Proven excellent problem-solving and analytical skills Proficiency in frameworks such as Scikit Learn, TensorFlow, and PyTorch Solid programming skills in Python, with experience in pandas, numpy, and SQL Ability to work in a fast-paced, dynamic environment Robust data engineering skills in EDA, building and maintaining AI/ML data pipelines Solid communication and interpersonal skills Preferred Qualification: Degrees, Diploma or Certifications in the field of AI/ML

Roles & Responsibilities : Must Have : Gen AI with experience AWS Bedrock Work Mode : Hybrid Location : Bangalore Design, develop, and optimize generative AI models using AWS Bedrock. Collaborate with cross-functional teams to understand project requirements and deliver AI-driven solutions. Conduct research and stay up-to-date with the latest advancements in generative AI and machine learning. Implement and maintain AI-centric libraries and frameworks such as langchain, langraph etc Perform data pre-processing, augmentation, and generation of synthetic data to enhance model performance. Evaluate and fine-tune AI models to ensure high-quality, creative content generation. Utilize AWS Bedrock to experiment with and evaluate top foundation models, customize them with your data, and build agents that execute tasks using your enterprise systems and data sources. Document and present findings, methodologies, and results to stakeholders. Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI model performance and accuracy.