Anduril Industries
Applied LLM Systems Engineer
About this role
Anduril seeks an Applied LLM Systems Engineer to design and operate production AI systems that automate and enhance technical documentation workflows. This is a systems engineering role requiring proven experience delivering production AI systems, with a focus on cost optimization, safety, observability, and integration with enterprise content platforms in a defense technology context.
What you'll do
- Build production-grade LLM applications for documentation and knowledge-work automation pipelines
- Design multi-step orchestration workflows coordinating models, tools, and deterministic services with safety guarantees
- Optimize token usage, context management, caching, and workflow design for cost and latency at scale
- Create evaluation frameworks, regression tests, and observability systems for AI-assisted workflows
- Establish rollback mechanisms, auditability, and safe failure modes for nondeterministic systems
- Collaborate with technical writers and engineering teams to identify appropriate AI applications and maintain human oversight where needed
What they're looking for
- Production AI/LLM systems engineering and deployment
- Python and modern software architecture practices
- LLM orchestration, RAG, tool calling, and structured outputs
- Cost and latency optimization for language models
- Evaluation design and regression testing for probabilistic systems
- Cloud infrastructure, containerization, CI/CD, and monitoring
- Security, identity management, and data protection
- Technical judgment on appropriate AI versus deterministic/human workflows
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Anduril Industries
Anduril Industries builds autonomous defense systems including underwater vehicles, unmanned aircraft, and electronic warfare platforms for the Department of Defense. The company is hiring across mechanical engineering, mission operations, software development, technical leadership, and advanced manufacturing roles to support the design, deployment, and production of these mission-critical systems.
- Website
- anduril.com
Likely interview questions
- Walk us through a production AI system you've built—what were the key challenges optimizing cost and latency, and how did you measure success?
- How have you approached evaluation and rollback strategies when deploying nondeterministic systems to production?