Agentic AI Developer – Python
Indexed description
Job Title: Agentic AI Developer – Python
Location: Boston, MA
About the Role
We are looking for a skilled Python developer with deep expertise in building autonomous AI agent systems. You will design, develop, and deploy agentic AI solutions that leverage large language models (LLMs) to autonomously plan, reason, and execute complex tasks using tool integrations and multi-agent orchestration.
Key Responsibilities
- Design and develop AI agents using Python frameworks such as PydanticAI, LangGraph, LangChain, CrewAI, or AutoGen
- Build multi-agent workflows with planning, reasoning, reflection, and tool-use capabilities
- Integrate agents with enterprise tools via Model Context Protocol (MCP), REST APIs, and SDKs
- Develop and deploy agentic applications on AWS Bedrock AgentCore and/or Azure OpenAI
- Implement RAG (Retrieval-Augmented Generation) pipelines for grounding agent responses
- Design structured outputs using Pydanticmodels for validation and schema enforcement
- Build evaluation frameworks (LLM-as-Judge, unit testing, compiler validation) for agent quality
- Implement observability, tracing, and monitoring for agent workflows in production
- Collaborate with platform engineering, security, and DevOps teams for production deployment
- Apply responsible AI principles, guardrails, and security controls to agent systems
Required Qualifications
- 5+ years of hands-on Python development experience
- 2+ years experience with LLM-based application development (prompt engineering, chains, agents)
- Strong proficiency in Python frameworks: FastAPI, Pydantic, asyncio
- Experience with at least one agentic AI framework: PydanticAI, LangGraph, LangChain, CrewAI, AutoGen, or Semantic Kernel
- Working knowledge of LLM APIs: OpenAI, AWS Bedrock, Azure OpenAI, Anthropic
- Experience building RAG systems with vector databases (Pinecone, Weaviate, FAISS, OpenSearch)
- Familiarity with MCP (Model Context Protocol) for tool/service connectivity
- Understanding of agent patterns: ReAct, function calling, tool use, planning/decomposition, multi-agent orchestration
- Experience with CI/CD pipelines, Git, containerization (Docker/Kubernetes)
- Cloud platform experience: AWS (Bedrock, Lambda, SageMaker, DynamoDB) and/or Azure (OpenAI, Cognitive Services, Cosmos DB)
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