Anduril Industries
Mission Software Engineer - Undersea Reconnaissance & Strike
About this role
Anduril Maritime seeks a Mission Software Engineer to debug and fix real-world issues in autonomous underwater/surface vehicles deployed in the field. You'll reproduce field-reported anomalies, use observability tooling to reconstruct system state, implement fixes across multiple languages, and document root causes to improve future reliability.
What you'll do
- Reproduce field-reported anomalies using recorded sensor/mission data and visualization tooling instead of guessing
- Use metrics, dashboards, and centralized logs to reconstruct system state at failure moments
- Implement fixes in the actual subsystem language (Rust, C++, Python, Go) with tests and CI/CD
- Distinguish between bugs, misconfigurations, and deployment mismatches and fix at the appropriate layer
- Document root causes and build on-call/triage runbooks to prevent recurring issues
- Travel 25%+ to support field operations and work alongside hardware/sensor deployments
What they're looking for
- Debugging unfamiliar code under time pressure with incomplete information
- Proficiency in at least two of: Rust, modern C++, Python, Go
- Systems debugging with logs, metrics, and offline data replay
- Observability platforms (Prometheus/Grafana, Loki/ELK)
- Linux and systems-level fluency
- Technical writing and clear root-cause documentation
- Hardware-in-the-loop and simulation testing
- CI/CD and versioned deployment practices
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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 time you debugged a production issue in code you didn't write—what was your process and how did you handle incomplete information?
- How would you approach reproducing a field-reported sensor anomaly if you couldn't immediately replicate it live?