We are looking for a Generative AI Tech Lead and Developers to provide technical leadership and architectural direction for building and operating production-grade GenAI solutions on AWS. This role combines hands-on development, solution architecture, team mentorship, and operational ownership. Team will own end-to-end delivery of GenAI platforms using Python, AWS Bedrock (Agent Core SDK), AWS Strands SDK, and modern DevOps and observability practices, ensuring scalability, security, reliability, and cost efficiency. Solid understanding of LLMs(Anthropic (Claude LLM)), embeddings, prompts, tokens, latency, cost factors Practical experience with RAG architectures, vector stores, and grounding strategies Ability to select and justify model choices (open-source vs proprietary) Experience supporting real-world use cases, not just POCs or demos Experience in AWS bedrock platform using Python, Strands SDK Multi-Agents, LangGraph/CrewAIKey Responsibilities Generative AI Development Design and implementGenerative AI applicationsusingAWS Bedrock , including: oBedrock Agent Core SDK oFoundation Models (FM) integration oPrompt engineering and agent orchestration Build AI workflows usingAWS Strands SDKfor scalable model execution and orchestration Develop and maintain reusableAI components, APIs, and servicesin Python Optimize model performance, latency, and cost for production workloadsAWS-Native Application Development Design and developcloud-native applicationson AWS using: oAWS Lambda, ECS/EKS, EC2 oAPI Gateway / Application Load Balancer oS3, DynamoDB, Aurora, OpenSearch Implement secure IAM roles and policies aligned with least-privilege principles Build event-driven and microservices-based architecturesDevOps & CI/CD Design and maintainCI/CD pipelinesusing tools such as: AWS CodePipeline / CodeBuild / CodeDeploy oGitHub Actions / GitLab CI (as applicable) Infrastructure as Code (IaC) using: AWS CloudFormation / CDK / Terraform Automate build, test, deployment, and rollbacks for GenAI workloadsObservability & Operations Implement end-to-endobservabilityfor AI and application workloads: Amazon CloudWatch (logs, metrics, alarms) oAWS X-Ray tracing oCustom metrics for model behavior and performance Monitor: Model response latency oToken usage and cost oError rates and failure scenarios Participate inincident management , root cause analysis, and system optimizationSecurity, Governance & Compliance Ensure secure handling of data used in AI workflows Implement: Encryption at rest and in transit oSecure secrets management (AWS Secrets Manager / Parameter Store) Follow enterprise standards for: Data privacy oAI governance oResponsible AI usageRequired Skills & Qualifications Technical Skills (Must Have)• Python(advanced proficiency) Hands-on experience with: oAWS Bedrock oAWS Bedrock Agent Core SDK oAWS Strands SDK Strong knowledge ofAWS servicesand cloud-native design patterns Experience building and deploying applicationsnatively on AWS CI/CD pipeline implementation and maintenance Observability and monitoring in production environmentsPreferred Skills (Good to Have) Experience with: LLMs, RAG (Retrieval Augmented Generation) Vector databases and embeddings Knowledge of containerization: Docker, Kubernetes (EKS) Familiarity with MLOps or Model Lifecycle Management Experience with cost optimization for AI workloads Understanding of ethical AI and responsible AI principlesPlease share resume suchi.srivastava@ with Details:Current CTC: Expected CTC: Notice period: Total Gen Ai Exp: AWS Bedrock Exp: SDK/ Agen Rock Exp: Python Engineering Exp:
Job Title
Gen AI Lead