Gen AI Lead

• 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/CrewAI

Key Responsibilities Generative AI Development

• Design and implement Generative AI applications using AWS Bedrock , including:

o Bedrock Agent Core SDK o Foundation Models (FM) integration oPrompt engineering and agent orchestration

• Build AI workflows using AWS Strands SDK for scalable model execution and orchestration
• Develop and maintain reusable AI components, APIs, and services in Python
• Optimize model performance, latency, and cost for production workloads

AWS-Native Application Development

• Design and develop cloud-native applications on AWS using:

o AWS Lambda, ECS/EKS, EC2 o API Gateway / Application Load Balancer o S3, DynamoDB, Aurora, OpenSearch

• Implement secure IAM roles and policies aligned with least-privilege principles
• Build event-driven and microservices-based architectures

DevOps & CI/CD

• Design 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 / Terraform
• Automate build, test, deployment, and rollbacks for GenAI workloads

Observability & Operations

• Implement 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 performance
• Monitor:
• Model response latency o Token usage and cost o Error rates and failure scenarios
• Participate in incident management , root cause analysis, and system optimization

Security, Governance & Compliance

• Ensure secure handling of data used in AI workflows
• Implement:
• 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 SDK

• Strong knowledge of AWS services and cloud-native design patterns
• Experience building and deploying applications natively on AWS
• CI/CD pipeline implementation and maintenance
• Observability and monitoring in production environments

Preferred 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 principles

Please share resume with Details:

Current CTC:

Expected CTC:

Notice period:

Total Gen Ai Exp:

AWS Bedrock Exp:

SDK/ Agen Rock Exp:

Python Engineering Exp: