Applied LLM Systems Engineer

What you'll do

• Develop LLM applications and orchestration workflows for documentation, coordinating models, tools, and deterministic services safely.
• Optimize cost, latency, context usage, and task success; establish evaluation, observability, rollback, and safe failure handling.
• Integrate AI with enterprise content and documentation systems while preserving provenance and working with documentation teams.

What they ask for

• 5+ years of professional software engineering experience, including building and operating production services.
• Direct experience delivering at least one production AI system with measurable adoption by its intended users.
• Experience optimizing cost, latency, and context usage in production LLM or workflow systems, and designing evaluation, observability, rollback, and failure-handling for nondeterministic systems.
• Strong proficiency in Python and modern API, data, and service-development practices; must be eligible for Secret and higher security clearance (US).

Nice to have

• Experience with multi-step orchestration, retrieval-augmented generation, structured outputs, or tool calling.
• Experience in regulated or documentation-heavy environments, or with S1000D, DITA, or MIL-STD-40051.

Pay

$191,000 — $254,000 USD (base salary)

Tools

Python, S1000D, DITA, MIL-STD-40051

AI focus

Build production LLM systems for technical documentation, including authoring assistance, automated publishing, retrieval, structured outputs, tool integration, multi-step orchestration, and evaluation.