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Senior, niche LLM/agent specialization but global brand increases applicant interest.
Requires production LLM and agent orchestration experience, making backgrounds without ML/LLM exposure a poor fit.
Explicit 9+ years plus mandatory LLM, async Python, cloud, and observability skills enforce strict filters.
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Design, build, and deploy autonomous multi-agent workflows with complex orchestration involving conditional routing, parallel execution, and error recovery across multiple business domains.
Develop production-grade async FastAPI applications integrating cloud LLM providers, real-time streaming, observability, and enterprise security compliant with data governance and Responsible AI standards.
Lead development of reusable agent node libraries, evaluation frameworks for agent performance, and mentor junior engineers while collaborating with cross-functional teams to translate requirements into scalable solutions.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related discipline.
9+ years of software engineering experience with at least 2 years building and deploying production LLM-powered applications.
Proven experience with agent orchestration frameworks (LangGraph preferred), cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4), and async Python (asyncio, FastAPI).
Experience with Docker, Git, CI/CD pipelines, cloud platforms (AWS, Azure, or GCP), and knowledge of agentic design patterns including ReAct, Plan-and-Execute, and tool use agents.
Senior software engineer with deep expertise in building complex autonomous multi-agent AI systems involving advanced orchestration and real-time streaming architecture.
Experience working at scale integrating multiple cloud LLM providers with observability tooling and enterprise-grade security in regulated environments.
Proven ability to lead and mentor teams, collaborate across global and cross-functional teams, and align AI/ML technical design with business domain needs.