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Tier-1 employer and metro location but highly specialized principal ML/AI role limits qualified applicant pool.
Specialized LLM and agent-engineering skills limit cross-industry transferability.
Explicit 9+ years, 2+ LLM years, and many mandatory LLMOps, async Python, cloud, and framework requirements.
Design, build, and deploy autonomous multi-agent workflows using orchestration frameworks like LangGraph, including complex state machines and error recovery.
Architect and maintain graph-based agent workflows with 10+ nodes involving agent collaboration and multi-domain task execution.
Develop production-grade async FastAPI applications integrating cloud LLM providers and implement observability and evaluation frameworks for agent performance and cost optimization.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related discipline.
9+ years of software engineering experience, with 2+ years in production LLM-powered applications.
Proven expertise in agentic orchestration frameworks (e.g., LangGraph, LangChain), cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, GPT-4), async Python programming, and production async web frameworks (FastAPI).
Experience with cloud platforms (AWS, Azure, or Google Cloud), Docker, Git, CI/CD pipelines, and enterprise security integration.
Experienced in building autonomous multi-step LLM agent systems with advanced features like conditional logic, state management, and tool-calling patterns.
Strong background in agentic design patterns (ReAct, Plan-and-Execute), LLMOps practices, observability tooling, and prompt engineering at scale.
Ability to collaborate with global, distributed teams and mentor junior engineers in async Python and LLM agent development.