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Staff AI & Agentic Platform Engineer

Anduril· AFS : Discovery Engineering : Frontier AI
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Hybrid (Costa Mesa, CA), Hybrid (Washington, DC)$253k - $336kFull-timePosted 1w ago

About the role

Discovery is building an expeditionary AI team focused on taking AI models from research into production for classified platforms and edge hardware. The role centers on evaluating, validating, and deploying agentic AI and ML models, building evaluation infrastructure, and ensuring reliable performance in real-world, security-sensitive environments.

Responsibilities

  • Develop Test Scenarios Simulation Environments: Develop comprehensive test scenarios, and simulation environments to assess agentic AI performance in classified simulations.
  • Validate AI on Classified & Edge Platforms: Lead the integration and validation of agentic AI systems onto classified platforms and edge hardware.
  • Build Reusable Evaluation Pipelines: Build reusable evaluation pipelines, automated test harnesses, and monitoring dashboards for continuous validation.
  • Define Actionable Metrics: Figure out what good metrics look like for AI models and traditional models—establishing systematic, historic capture of performance rather than one-shot, deployment-specific measurement.
  • Partner Cross-Functionally: Partner with cross-functional teams to define requirements, document test results, and contribute to AI model cards and deployment readiness reviews.
  • Own End-to-End Evaluation: Architect, build, and maintain the evaluation and validation infrastructure for our agentic AI and ML models, from unit-level model checks through full-system, scenario-based assessment.
  • Troubleshoot and Debug: Analyze and resolve issues uncovered in evaluation and in deployment, ensuring reliability and operational success across every release.

Qualifications

  • 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 for building evaluation pipelines, test harnesses, and tooling.
  • Demonstrated experience owning evaluation or automated testing for production ML or software systems—test scenarios, metrics, regression suites, and CI infrastructure.
  • Hands-on experience designing evaluation methodologies for AI or machine learning models—defining metrics, building benchmarks, and assessing model behavior against real-world scenarios.
  • Experience designing or working extensively with simulation environments to exercise model and system behavior.
  • Working knowledge of how to define, capture, and reason about performance metrics for AI models and traditional models, including systematic historic capture over time.
  • Ability to navigate and contribute to complex systems and established codebases.
  • Comfort operating between technical program management and software engineering—defining requirements, coordinating across teams, and documenting results.
  • Passion for building the evaluation infrastructure that proves AI works—directly influencing mission-critical outcomes.
  • Must have a TS/SCI security clearance.

Skills

Required:PythonEvaluation & Testing for ML/AISimulation EnvironmentsSystem & Hardware IntegrationCI/CD & AutomationCommunication & Collaboration

Benefits

  • Comprehensive, competitive benefits package (health, recovery, and more) available to full-time employees.
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Anduril

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