Key Responsibilities Design, develop, and deploy LangGraph-based agentic systems that orchestrate LLM-driven tools and workflows. Build and integrate modular AI agents capable of real-world task execution in cloud-native environments. Utilize AWS services such as Lambda, Step Functions, Bedrock, S3, ECS/Fargate, DynamoDB, and API Gateway to support scalable, serverless infrastructure. Write production-grade Python code, following best practices in software design, testing, and documentation. Build robust CI/CD pipelines and advocate for DevOps and Infrastructure as Code (IaC) practices using tools like CDK or Terraform.Minimum Requirements 5+ years of experience as a Software Engineer, with at least 2 years in AI/ML or LLM-centric development. Proven track record with LangGraph, LangChain, or similar orchestration frameworks. Expert in Python (asyncio, FastAPI preferred). Hands-on experience building and deploying applications on AWS, particularly using Lambda, Fargate, S3, Step Functions, and DynamoDB. Familiarity with AWS Bedrock is a plus. Strong understanding of agentic patterns, prompt chaining, tool calling, and memory/state management in LLM applications. Solid experience with unit and integration testing, CI/CD, and GitOps practices.Preferred Qualifications Experience designing and scaling multi-agent systems or tool-augmented LLM workflows. Familiarity with secure cloud development practices and IAM role design. Understanding of LLM fine-tuning, embeddings, vector st