Software Engineer, Verification & Validation
FieldAI· Engineering – Systems Engineering
Irvine, CA$135k - $190kFull-timePosted 3mo ago
About the role
Field AI is building risk-aware, reliable, and field-ready AI systems for robotics. This role focuses on end-to-end verification & validation of robotic systems, building scalable test infrastructure, validating real-world robot behavior, turning failures into engineering signals, and driving system reliability and release readiness.
Responsibilities
- Own End-to-End Robot Verification & Validation - Design and execute verification and validation strategies for complete robotic systems, from individual capabilities through full autonomous missions
- Develop clear acceptance criteria, performance metrics, and test methodologies for new robot capabilities
- Validate system behavior across multiple robotic platforms, environments, and operating conditions
- Build repeatable qualification and regression processes that allow new capabilities to ship without compromising existing functionality
- Establish a clear understanding of what “deployment-ready” means and provide quantitative evidence that systems meet that bar.
- Build Scalable Robotics Test Infrastructure - Develop automated test infrastructure spanning simulation, hardware-in-the-loop, lab testing, and full robot operation
- Create reusable test scenarios and evaluation frameworks that exercise autonomy under nominal, edge-case, and failure conditions
- Build tools for experiment execution, telemetry collection, automated analysis, visualization, and reporting
- Improve the reproducibility of robot testing so failures can be recreated, diagnosed, and verified efficiently
- Help move validation from individual one-off tests toward continuously running, scalable system evaluation
- Validate Real-World Robot Behavior - Design tests that expose robots to uncertainty and variability in real deployments
- Exercise systems across changing terrain, obstacles, environmental conditions, sensor degradation, communication failures, compute limitations, and other disturbances
- Evaluate not only success but reliability, safety, and consistency across repeated trials
- Identify performance boundaries and characterize degradation points
- Work directly with physical robots in lab and field to reproduce difficult system-level failures
- Turn Failures Into Engineering Signal - Debug failures across autonomy, sensing, state estimation, planning, control, system integration, compute, networking, and hardware boundaries
- Use telemetry and data to isolate root causes
- Develop tooling and instrumentation to understand complex robot behavior
- Convert field failures into deterministic regression tests when possible
- Partner with subsystem owners to verify fixes and prevent recurrence
- Drive System Reliability and Release Readiness - Partner with autonomy, robotics software, hardware, systems, and field teams
- Identify integration and reliability risks early and reflect them in validation
- Build dashboards, scorecards, and automated evaluations for system health and capability maturity
- Help define release gates based on measurable system performance
- Continuously improve the V&V process as systems evolve
Qualifications
- Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or related field, or equivalent hands-on industry experience
- Strong software engineering fundamentals with proficiency in C, C++, and Python for developing, integrating, debugging, and testing robotic systems
- Hands-on experience developing, integrating, testing, or debugging physical robotic or autonomous systems
- Broad understanding of robotic systems including sensing, state estimation, planning, control, communication, compute, and actuation
- Experience developing and debugging robotics software using ROS 2 and distributed message-passing architectures
- Strong experience working in Linux environments, familiarity with real-time systems and RT-patched Linux kernels
- Proficiency with Git and modern collaborative software development practices, including code review, branching, integration, and regression workflows
- Experience diagnosing complex system-level failures where root causes span software, middleware, networking, compute, sensors, and hardware
- Experience designing quantitative experiments, defining performance metrics, and analyzing robot telemetry and test data
- Strong instincts for testability, observability, reproducibility, and systematic debugging
Skills
Required:CC++PythonROS 2LinuxSystem-level debugging
Nice to have:Telemetry
Benefits
- Full benefits
- Equity
- Generous time off
Last updated Oct 22, 2026. Interested? Apply on the company site.
About FieldAI
Robot intelligence built for the real-world.
FieldAI is the leader in deploying general-purpose robots in unstructured environments, providing a universal brain that works across many robots, and many tasks.
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