NICE TO HAVE LangChain / Strands: Familiarity with orchestration and agent frameworks for building LLM applications and pipelines AWS CDK: Infrastructure-as-code experience for defining and deploying cloud resources in Python or TypeScript CI/CD basics: Exposure to automated testing, deployment pipelines, or GitHub Actions Streamlit: Ability to build lightweight internal tools and data apps for rapid prototyping LLM API advanced patterns: Deep familiarity with tool use, streaming, function calling, and structured outputs Vector databases: Experience with embeddings storage and retrieval (e.g., Pinecone, pgvector, Weaviate) Snowflake Cortex / ML features: Experience using Snowflake's native ML and AI capabilities for in-warehouse inference. WHAT YOU WILL DO Agentic AI & client tools: Design, build, and deploy serverless LLM-powered agents and MCP servers on AWS Lambda, integrating tool use, RAG, and multi-agent communication patterns; translate client requirements into working AI tools, demo and iterate based on feedback, and help scale pilots to production.