AI & Agentic Platform

Costa Mesa · Washington · Washington, DC (DC-01) · USD 253,000-336,000 · 8-10 years experience · Full-time · Posted Oct 8, 2026

At a glance

The Discovery team at Anduril is seeking an engineer to build the evaluation and validation infrastructure for agentic AI and ML models.
This role focuses on taking AI models from research into production on classified platforms and edge hardware.
You will architect and maintain evaluation pipelines, test harnesses, and simulation environments to ensure reliable performance in real-world scenarios.

Develop comprehensive test scenarios and simulation environments to assess agentic AI performance in classified simulations.
Lead the integration and validation of agentic AI systems onto classified platforms and edge hardware.
Build reusable evaluation pipelines, automated test harnesses, and monitoring dashboards for continuous validation.
Define actionable metrics for AI and traditional models to establish systematic, historic capture of performance.
Partner with cross-functional teams to define requirements, document test results, and contribute to AI model cards and deployment readiness reviews.
Architect, build, and maintain the evaluation and validation infrastructure from unit-level checks through full-system assessment.
Analyze and resolve issues uncovered in evaluation and deployment to ensure operational success.

Bachelor's or Master's degree in Computer Science, Machine Learning, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical field.
At least 8-10 years of hands-on experience writing production-grade code, with strong Python skills.
Demonstrated experience owning evaluation or automated testing for production ML or software systems.
Hands-on experience designing evaluation methodologies for AI or machine learning models.
Experience designing or working extensively with simulation environments.
Working knowledge of how to define, capture, and reason about performance metrics for AI and traditional models.
Ability to navigate and contribute to complex systems and established codebases.
Comfort operating between technical program management and software engineering.
Must have a TS/SCI clearance.

Experience as an ML Test & Evaluation Engineer, SDET for ML systems, ML/Evaluation Engineer, Simulation Engineer, or Technical Program Manager for AI/ML.
Experience designing test methodologies for agentic AI systems.
Familiarity with validating and deploying AI models onto classified platforms, edge hardware, or resource-constrained environments.
Experience contributing to AI model cards, deployment readiness reviews, or similar model-governance practices.
Familiarity with test and evaluation practices in aerospace or defense.
Experience with MLOps tooling, monitoring dashboards, and continuous validation pipelines.
Experience with Go, C++, or scripting for test automation and tooling.
Interest in growing from T&E ownership into deeper ownership of the AI evaluation and deployment stack.