<p>AWMust Have Technical/Functional Skills</p> <ul> <li>10+ years of experience in Software Development & ML engineering, including 4+ years in Solution architecture or </li></ul> <p>AI architecture delivering production-grade systems.</p> <ul> <li>Strong hands-on expertise in Python (workflow orchestration, model evaluation), Node.js, and experience working </li></ul> <p>with agent-based frameworks such as AutoGen, LangChain, or ADK. Solid knowledge of prompt engineering techniques</p> <p>and tool-calling mechanisms.</p> <ul> <li>Deep understanding of retrieval-augmented systems, including embeddings, chunking strategies, ranking mechanisms, </li></ul> <p>and Vector databases such as Qdrant and MongoDB Atlas with vector search capabilities.</p> <ul> <li>Extensive experience in MLOps practices, including CI/CD pipelines for ML models, model registry management, </li></ul> <p>and containerized deployments using Kubernetes.</p> <ul> <li>Strong cloud expertise in AWS, with hands-on experience in services such as Amazon Bedrock, SageMaker, </li></ul> <p>AWS Lambda, and Amazon EKS.</p> <ul> <li>Demonstrated experience in implementing Responsible AI practices, security best practices </li></ul> <p>(encryption, secrets management, network isolation), and FinOps strategies for AI workloads, including cost</p> <p>and latency optimization.</p> <p>Roles & Responsibilities</p> <ul> <li>Architect and design an end-to-end solution for an AI-driven Retrieval-Augmented system. </li><li>Define and implement the embedding strategy, document chunking methodology, and ranking techniques </li></ul> <p>to ensure high-quality retrieval.</p> <ul> <li>Evaluate, select, and integrate appropriate Large Language Models (LLMs) using Amazon Bedrock. </li><li>Design and implement a scalable vector database solution (such as OpenSearch, Qdrant, or MongoDB Atlas </li></ul> <p>with vector search).</p> <ul> <li>Architect and deploy the cloud infrastructure leveraging AWS services including Amazon Bedrock (LLM), SageMaker, </li></ul> <p>AWS Lambda, and Amazon EKS.</p> <ul> <li>Establish MLOps best practices by designing CI/CD pipelines for model deployment and managing model registry </li></ul> <p>updates.</p> <ul> <li>Apply FinOps principles to balance cost and performance, optimizing model size, inference latency, and </li></ul> <p>caching strategies.</p> <ul> <li>Design secure access controls and implement secrets management using AWS Secrets Manager. </li></ul> <p>Salary Range-$120,000-$140,000 a year</p> <p>#LI-KR3</p> <p>TCS Employee Benefits Summary:</p> <p>Discretionary Annual Incentive.</p> <p>Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.</p> <p>Family Support: Maternal & Parental Leaves.</p> <p>Insurance Options: Auto & Home Insurance, Identity Theft Protection.</p> <p>Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.</p> <p>Time Off: Vacation, Time Off, Sick Leave & Holidays.</p> <p>Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.</p>