Applied LLM Systems Engineer

What you'll do

• Build production-grade LLM applications for documentation and knowledge-work workflows.
• Design orchestration for multi-step workflows coordinating models, tools, and deterministic services.
• Optimize context management, token usage, and caching to manage costs and latency at scale.
• Develop retrieval, structured-output, and tool-integrated systems that interact with enterprise content and source control.
• Create evaluation frameworks and regression testing for prompts, models, and end-to-end workflows.
• Establish observability, auditability, and safe failure modes for AI-assisted processes.
• Maintain provenance between source material, generated output, and human decisions to ensure reviewable results.

What we're looking for

• Must have 5+ years of professional software engineering experience building and operating production services.
• Must have direct experience delivering at least one production AI system with measurable adoption by its intended users.
• Must have experience optimizing cost, latency, and context usage in production LLM or workflow systems.
• Must have experience designing evaluation, observability, rollback, and failure-handling for nondeterministic systems.
• Must be proficient in Python and modern API, data, and service-development practices including security and identity management.
• Must be eligible for Secret and higher security clearance (US).
• Experience designing multi-step orchestration or coordination systems across models, tools, and deterministic services (preferred).
• Experience with RAG, structured outputs, tool calling, or other production LLM workflow patterns (preferred).