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Metro location and broad LLM/AI skillset increase competition despite senior specialization.
Highly specialized LLM, agent-orchestration and regulated enterprise experience limits cross-industry transferability.
Explicit 9+ years, 2+ years production LLM experience and specific LLM/agent tech requirements enforce strict shortlisting.
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Design, build, and deploy autonomous multi-agent workflows and FastAPI-based applications integrating cloud LLM services and enterprise systems.
Develop and maintain reusable agent components, prompt management, observability, evaluation frameworks, and ensure security and compliance for generative AI solutions.
Collaborate with cross-functional teams and mentor junior engineers in async Python, LLMOps practices, and agentic system design.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related field.
9+ years software engineering experience; 2+ years building and deploying production LLM-powered applications.
Proven expertise with agentic orchestration frameworks (e.g., LangGraph), cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4), async FastAPI, Docker, CI/CD, and cloud platforms (AWS/Azure/GCP).
Work Experience Required: 9+ years software engineering, 2+ years with generative AI/LLM production apps; Notice period: Not explicitly mentioned in the JD.
Senior-level engineer experienced in architecting complex, multi-step autonomous AI agent workflows in regulated enterprise environments.
Proficient in advanced async Python programming, LLMOps best practices, and integrating observability and security in AI platforms.
Familiar with global life sciences domain (preferably GPS) and collaborating with distributed and offshore development teams.