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Medium — strong employer brand and metro location, but seniority and niche LLM/agent skills limit pool.
High — specialized LLM/agent engineering and enterprise compliance reduce cross-industry transferability.
High — explicit 9+ years, mandatory LLM production experience, and specific tech/security requirements.
Design, build, and deploy complex autonomous multi-agent workflows using orchestration frameworks like LangGraph, including state management, error recovery, and parallel execution.
Develop production-grade async FastAPI applications integrating databases (PostgreSQL, Redis) and cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4).
Implement observability, evaluation, security, and Responsible AI standards, and mentor junior engineers while collaborating cross-functionally to deliver scalable agent workflows.
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 in production LLM-powered application development.
Proven expertise with agentic orchestration frameworks (LangGraph preferred), async Python (asyncio, async/await), FastAPI, Docker, cloud platforms (AWS/Azure/GCP), and LLM providers integration.
Experience with agentic design patterns (ReAct, Plan-and-Execute), Model Context Protocol, agent-to-agent communication, prompt engineering, observability tools (Langfuse, LangSmith).
Senior engineer with deep specialization in autonomous multi-agent systems and orchestrations involving complex workflows with error recovery and conditional logic.
Highly skilled in async programming and production API development with strong understanding of agentic AI design and LLMOps practices.
Experience collaborating with global, distributed teams and managing cross-functional partnerships, ideally with exposure to life sciences or regulated environments.