Senior Quality Engineer, Applied AI Software

Senior Quality Engineer, Applied AI Build and own end-to-end automated system integration tests for production product lines

Location:

Costa Mesa, California

Compensation: $191, USD / year

Costa Mesa, California, United States

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century's most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center.

As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

Mission Control is the team responsible for quality assurance, release management, and incident management across the systems Anduril's factories run on. When a product line moves from design to a finished article, it crosses PLM, ERP, MES, and WMS, and the seams between them are where quality is won or lost. This role is the senior technical anchor for proving those seams hold.

You will build the automated system integration tests that exercise real product lines end to end, simulate the workload and data of a live production environment, and make it possible for the engineers and operators closest to the work to verify quality themselves.

• Design, build, and own automated system integration tests that exercise Anduril product lines end to end across multiple systems, rather than validating single services in isolation.
• Simulate production workload and data for those product lines so tests reflect what the factory actually does, and build mechanisms that detect when the simulation drifts from reality.
• Leverage AI to author, maintain, and triage tests faster, and turn that into capability for others so the people closest to the problems can ensure quality themselves.
• Reason about distributed architecture and reconcile intent, implementation, and observed production reality, tracing failures across service, network, and vendor boundaries to the actual cause.
• Set test strategy, release readiness criteria, and quality gates for the release train, and make them fast enough that teams choose to use them.
• Build the observability, instrumentation, and environment strategy that turn a failing test or a production incident into a clear, actionable signal.
• Partner with the engineering teams that own the systems under test, and with business partners on the floor, to move quality upstream into design and acceptance criteria.
• Contribute directly in code, infrastructure, and tooling to improve developer feedback loops, test reliability, and production stability.
• Support launch readiness, production issue response, root cause analysis, and post-incident follow-through, with a bias toward eliminating classes of failure rather than repeatedly reacting to them.
• Set the technical standard for testing craft across Mission Control through review, pairing, and example, without becoming a bottleneck or a bureaucracy.

• 8+ years of experience in software engineering, software development engineering in test, site reliability engineering, quality engineering, infrastructure engineering, or a closely related role in a fast-paced environment.
• Demonstrated experience building and operating automated integration or end-to-end test suites for production systems, including ownership of environments, test data, and CI execution.
• Strong technical fluency in modern software architectures, APIs, distributed systems, CI/CD, and cloud or platform infrastructure.
• Experience reasoning about failures that cross system boundaries, with strong debugging, root cause analysis, and incident response instincts.
• Experience working with frontier AI tooling, AI coding assistants, or agentic systems, including awareness of the quality and reliability challenges these systems introduce.
• Ability to move between hands-on implementation and systems-level quality strategy, with sound judgment on where rigor is required versus where speed is appropriate.
• Excellent written and verbal communication skills, with the ability to influence senior engineers, cross-functional stakeholders, and business partners on quality and reliability trade-offs.
• Degree in Computer Science, Information Systems, Engineering, or related technical field, or equivalent practical experience.
• U.S. Person status is required as this position needs to access export controlled data.

• Experience testing enterprise or manufacturing systems such as ERP, MES, WMS, PLM, or CRM, particularly workflows that span several of them.
• Experience generating or anonymizing…