Python | FastAPI | Docker | AWS SageMaker | LangChain | LangGraph | CrewAI | AutoGen | OpenAI | Anthropic | Azure OpenAI | AWS Bedrock | Prompt Engineering | RAG | Pinecone | FAISS | pgvector | Model Context Protocol | REST APIs | Snowflake Cortex AI | LangSmith | Ragas
Design and deliver agentic AI solutions that automate and enhance data and analytics workflows, taking ideas from prototype to production. Key Responsibilities • Design and build agentic AI solutions, including multi-agent workflows, tool use, planning, and memory • Develop LLM-powered use cases such as text-to-SQL, data quality agents, pipeline monitoring and self- healing, and documentation automation • Build RAG pipelines and integrate agents with Snowflake (Cortex) and enterprise data sources • Evaluate agent accuracy and reliability, and apply guardrails, observability, and responsible AI practices • Expose agents through APIs and integrate them with existing platform tools and workflows • Prototype new ideas quickly, run proofs of concept, and take successful ones to production • Track emerging AI trends and recommend tools and approaches suited to the team • Promote AI adoption through demos, documentation, and knowledge sharing
Required Skills • Agentic frameworks: LangChain, LangGraph, CrewAI, AutoGen • LLM APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock) and prompt engineering • Python, RAG, and vector databases (Pinecone, FAISS, pgvector) • MCP (Model Context Protocol) and REST APIs • Snowflake Cortex AI • LLM evaluation and observability tools (LangSmith, Ragas) • FastAPI, Docker, AWS SageMaker