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 factorsPractical experience with RAG architectures, vector stores, and grounding strategiesAbility to select and justify model choices (open-source vs proprietary)Experience supporting real-world use cases, not just POCs or demosExperience in AWS bedrock platform using Python, Strands SDK Multi-Agents, LangGraph/CrewAIKey Responsibilities Generative AI DevelopmentDesign and implement Generative AI applications using AWS Bedrock, including: o Bedrock Agent Core SDK o Foundation Models (FM) integration oPrompt engineering and agent orchestrationBuild AI workflows using AWS Strands SDK for scalable model execution and orchestrationDevelop and maintain reusable AI components, APIs, and services in PythonOptimize model performance, latency, and cost for production workloads AWS-Native Application DevelopmentDesign and develop cloud-native applications on AWS using: o AWS Lambda, ECS/EKS, EC2 o API Gateway / Application Load Balancer o S3, DynamoDB, Aurora, OpenSearchImplement secure IAM roles and policies aligned with least-privilege principlesBuild event-driven and microservices-based architectures DevOps & CI/CDDesign and maintain CI/CD pipelines using tools such as: AWS CodePipeline / CodeBuild / CodeDeploy o GitHub Actions / GitLab CI (as applicable)Infrastructure as Code (IaC) using: AWS CloudFormation / CDK / TerraformAutomate build, test, deployment, and rollbacks for GenAI workloads Observability & OperationsImplement end-to-end observability for AI and application workloads: Amazon CloudWatch (logs, metrics, alarms) o AWS X-Ray tracing o Custom metrics for model behavior and performanceMonitor: Model response latency o Token usage and cost o Error rates and failure scenariosParticipate in incident management, root cause analysis, and system optimization Security, Governance & ComplianceEnsure secure handling of data used in AI workflowsImplement: Encryption at rest and in transit o Secure secrets management (AWS Secrets Manager / Parameter Store)Follow enterprise standards for: Data privacy o AI governance o Responsible AI usage Required Skills & Qualifications Technical Skills (Must Have) •Python (advanced proficiency)Hands-on experience with: o AWS Bedrock o AWS Bedrock Agent Core SDK o AWS Strands SDKStrong knowledge of AWS services and cloud-native design patternsExperience building and deploying applications natively on AWSCI/CD pipeline implementation and maintenanceObservability and monitoring in production environments Preferred Skills (Good to Have)Experience with: LLMs, RAG (Retrieval Augmented Generation)Vector databases and embeddingsKnowledge of containerization: Docker, Kubernetes (EKS)Familiarity with MLOps or Model Lifecycle ManagementExperience with cost optimization for AI workloadsUnderstanding 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