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Metro location and strong employer brand but senior, niche AI/LLM role creates moderate competition.
Medium because LLM and engineering skills transfer across industries, though healthcare compliance adds domain specificity.
High due to explicit 9+ years requirement and mandatory LLM, agentic orchestration, and async Python expertise.
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Design, build, and deploy complex autonomous multi-agent workflows using orchestration frameworks like LangGraph, integrating LLMs and real-time streaming protocols.
Develop and maintain reusable agent node libraries, testing frameworks, and scalable FastAPI applications with integration to cloud services and databases.
Lead architecture decisions including observability, security, evaluation frameworks, and collaborate cross-functionally while mentoring junior engineers in async Python and LLMOps practices.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related field.
9+ years of software engineering experience with at least 2 years building production LLM-powered applications.
Proven expertise in agentic orchestration frameworks (e.g., LangGraph, LangChain), async Python (asyncio), FastAPI, cloud platforms (AWS, Azure, or GCP), and LLM providers (AWS Bedrock, Azure OpenAI, etc.).
Experience with Docker, Git, CI/CD, observability tooling (Langfuse, LangSmith), and enterprise security compliance.
Senior engineer with extensive experience in designing and deploying autonomous AI agent workflows in production environments.
Strong command of async Python programming, multi-agent system design patterns (ReAct, Plan-and-Execute), and LLMOps including prompt engineering and performance optimization.
Able to operate effectively in globally distributed teams and collaborate with cross-functional partners including data engineers, business analysts, and UX teams.