Lead Product Quality Engineer - Edge Compute and Comms

Anduril Anduril · Defense · Santa Ana, CA · Hardware Engineering : Quality Engineering : Quality Engineering

Lead Product Quality Engineer for Anduril's Edge Compute and Communications product portfolio, focusing on defining, developing, and executing processes to ensure high-quality and reliable products. This role involves technical leadership, root cause corrective action, design reviews, V&V testing, and FMEA, from concept through field use.

What you'd actually do

  1. Drive product improvement by implementing processes for data collection and incident reporting that will inform activities like detailed design reviews, process development, verification, validation, and qualification of processes and parts, and sub assemblies.
  2. Drive clarity & resolution for development ambiguities associated with product maturity, process stability, and field performance that impact the product meeting it's quality & reliability goals for volume production.
  3. Lead Root Cause and Corrective Action (RCCA) activities for field and reliability issues. Review the effectiveness of actions and share lessons learned across the product team.
  4. Champion the transition from new product introduction (NPI) to a sustainable & predictable product experience for our customers.
  5. Own the elimination of product risk to improve reliability across the product lifecycle. Engage in quality activities from concept through development and manufacturing to field use.

Skills

Required

  • Bachelor's degree in Engineering or similar technical field
  • 7+ years of experience in Engineering, Manufacturing, or Quality in aerospace/defense or similar complex hardware environments, including Edge Compute, Communications, or electronics products.
  • Demonstrated technical leadership experience, including mentoring, guiding, or leading a team of engineers (3-5 PQEs preferred) to ensure consistency and rigor across quality processes.
  • Proven experience leading root cause corrective action (RCCA) efforts for complex problems and issues, utilizing tools such as 8D, Lean Six Sigma, Fault Tree Analysis, and DMAIC methodologies.
  • Strong working knowledge of design review and quality management of PCBA, harnessing, machined & sheet metal components, and weldment structures.
  • Strong working knowledge of product development methodologies such as Failure Modes and Effects Analysis (FMEA), Verification & Validation (V&V) testing, Advanced Product Quality Planning (APQP), and Production Part Approval Process (PPAP) elements including Measurement Systems Analysis (MSA) and Geometric Dimensioning and Tolerancing (GD&T).
  • Working knowledge of mechanical and/or electrical manufacturing processes.
  • A strong ownership mindset with demonstrated capability to drive projects and teams from start to completion.
  • Analytical skills and experience with data mining, data quality, metrics generation, issue management systems, and statistical analysis tools (MATLAB, JMP, Minitab, etc.).
  • Excellent communication and collaboration skills, with the ability to influence cross-functional teams and drive alignment on quality standards.
  • Must be able to obtain and hold a U.S. security clearance.

Nice to have

  • Master's degree in a technical field
  • 10+ years of experience with developing quality systems for low volume, high complex manufacturing environments and suppliers.
  • Working knowledge of AS9100/ ISO 9001-based Quality Management System requirements.
  • Experience with IPC standards
  • Lean six sigma certification is preferred.
  • Experience with government contracts and mil standard or other regulatory requirements.
  • Experience with Teamce

What the JD emphasized

  • technical leadership
  • Root Cause Corrective Action (RCCA)
  • Verification & Validation (V&V) testing
  • Failure Mode and Effects Analysis (FMEA)
  • product quality
  • reliability goals
  • product risk
  • product lifecycle
  • quality activities
  • product roadmap
  • quality and the factors that predict quality performance
  • Quality Management System
  • manufacturing requirements
  • quality standards
  • product quality plans
  • design decisions based on data
  • DOE’s (Design Of Experiments)