Senior Quality Engineer, Applied AI
$146k - $194k • Seattle, Washington, United States
Posted 12d ago
Job Location
Seattle, Washington, United States
Tech Stack
Remote Work Policy
On-site
Categories
Applied AI Engineer
About the job
Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The CorpTech Platform team, an internal engineering force multiplier, drives innovation through strategic investments in data, software, QA, ERP, and AI infrastructure. This role is part of a team building the foundations for CorpOS and ArsenalOS, unifying systems and accelerating development velocity. We are also pioneering an autonomous enterprise by integrating AI directly into the engineering lifecycle, making this a strategic engine for scaling business systems with rigor and adaptability.
Responsibilities
- Lead quality and reliability for an AI development pod tackling high-impact problems.
- Design and implement test strategies, validation approaches, and release criteria for AI-enabled software and workflows.
- Collaborate with engineers to identify failure modes across code, prompts, models, integrations, infrastructure, and user workflows.
- Build confidence in solutions through automated testing, observability, instrumentation, and safeguards.
- Define practical standards for reliability, debugging, and AI-first development operations.
- Contribute code, infrastructure, and tooling to enhance delivery confidence and production stability.
- Support launch readiness, incident response, root cause analysis, and continuous improvement for delivered systems.
- Promote strong engineering discipline in quality assurance, release engineering, and incident prevention.
Requirements
- 5+ years of experience in software engineering, SRE, QA, or infrastructure engineering in a fast-paced environment.
- Proven experience building/operating reliable production software systems, including testing, observability, and operational readiness.
- Strong technical understanding of modern software architectures, APIs, distributed systems, CI/CD, and cloud infrastructure.
- Experience with frontier AI tooling, AI coding assistants, LLM-enabled applications, or agentic systems, and their unique quality challenges.
- Ability to balance hands-on implementation with systems-level quality strategy.
- Strong debugging, root cause analysis, and incident response skills.
- Excellent communication skills to influence stakeholders on quality trade-offs.
- Degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- U.S. Person status required for access to export-controlled data.