Principal Quality Engineering AI Lead

What you'll do

• Develop and implement AI/ML quality strategies and validation frameworks for missile solutions applications.
• Establish data governance practices including quality controls, labeling accuracy, drift monitoring, and bias prevention.
• Define measurable performance metrics and acceptance criteria for mission-critical AI systems.
• Lead verification and validation activities including adversarial testing, stress testing, and edge-case simulation.
• Adapt traditional risk tools like FMEA to address machine-learning-specific failure modes.
• Oversee quality frameworks for automated inspection systems and synthetic data pipelines.
• Govern post-deployment practices such as regression testing, drift thresholds, and retraining workflows.
• Align internal AI engineering practices with emerging standards like ISO/IEC 42001 and NIST AI RMF.

What we're looking for

• Bachelor’s Degree in Engineering, Computer Science, Data Science, Statistics, or related field with 12 years of experience.
• Graduate Degree in a related technical field with 10 years of experience.
• 16 years of related experience in lieu of a degree.
• Minimum 3 years of experience leading technical projects, cross-functional initiatives, or engineering teams.
• Minimum 1 year of experience in verification, validation, testing, or quality management of software-intensive systems, AI/ML models, or analytics pipelines.
• Ability to obtain and maintain a U.S. Security Clearance.
• Experience in manufacturing or quality in defense, aerospace, automotive, or similar industries (preferred).
• U.S. citizens.