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Salary: USD 191,000 - 253,000 / annual
Anduril Industries is seeking an Applied LLM Systems Engineer to design, build, and operate production AI systems that improve how technical documentation is created, transformed, validated, maintained, and delivered across defense and aerospace programs.
This is a systems-engineering role for someone with proven experience delivering production AI systems. You will not be writing prompts—you will be architecting and operating enterprise-grade LLM applications. Your mission is to build AI-assisted authoring, automated publishing, and multi-agent coordination tooling for the Technical Publications pipeline, handling complex workflows with strict review requirements, security boundaries, and real operational consequences.
Key responsibilities include:
- Design and build production-grade LLM applications for documentation and knowledge-work workflows
- Architect multi-step orchestration systems that safely coordinate models, tools, and deterministic services
- Optimize context management, token usage, caching, and workflow design for cost, latency, and task success
- Build retrieval-augmented generation, structured-output, and tool-integrated systems that interact securely with enterprise content, source control, issue tracking, and documentation systems
- Design evaluation frameworks and regression testing for prompts, models, tools, retrieval pipelines, and end-to-end workflows
- Establish observability, auditability, rollback mechanisms, and safe failure modes for AI-assisted workflows
- Collaborate directly with technical writers, illustrators, engineers, and documentation leadership to identify high-value AI applications and preserve human judgment where needed
- Maintain provenance between source material, generated output, validation results, and human decisions to ensure outputs remain reviewable, correctable, and attributable
Required qualifications: 5+ years of professional software engineering experience including production services; direct experience delivering at least one production AI system with measurable user adoption; experience optimizing cost, latency, and context usage in production LLM systems; experience designing evaluation, observability, rollback, and failure-handling for nondeterministic systems; strong Python proficiency and modern API/data/service-development practices; sound judgment about where probabilistic AI is appropriate versus deterministic software or human review; eligibility for Secret and higher US security clearance; subject to pre-employment and randomized substance screening.
Preferred qualifications include experience with multi-step orchestration systems, retrieval-augmented generation, structured outputs, tool calling, integrating AI into enterprise applications, defense/aerospace/manufacturing/regulated environments, technical documentation and structured authoring, S1000D/DITA/MIL-STD frameworks, containerized services, cloud infrastructure, CI/CD, and production monitoring.
