Senior Quality Engineer, Applied AI

Boston · Costa Mesa, CA (OC-00) · USD 146,000-194,000 · 5+ years experience · Full-time · Posted Sep 29, 2026

At a glance

Act as the quality and reliability lead within a small, senior AI development pod focused on solving novel, high-impact business and engineering problems.
Design and implement test strategies, validation approaches, and release readiness criteria for AI-enabled software, automation, and agentic workflows.

Act as the quality and reliability lead within a small, senior AI development pod focused on solving novel, high-impact business and engineering problems.
Design and implement test strategies, validation approaches, and release readiness criteria for AI-enabled software, automation, and agentic workflows.
Partner closely with software and AI engineers to identify failure modes early across code, prompts, models, integrations, infrastructure, and user workflows.
Build confidence in fast-moving solutions through automated testing, observability, instrumentation, environment design, and operational safeguards.
Help define practical standards for reliability, resiliency, debugging, and production operations in an AI-first development model.
Contribute directly in code, infrastructure, and tooling where needed to improve delivery confidence, developer feedback loops, and production stability.
Support launch readiness, production issue response, root cause analysis, and continuous improvement for front-facing systems delivered by the pod.
Evangelize strong engineering discipline in areas such as quality assurance, release engineering, infrastructure hygiene, and incident prevention without sacrificing speed.

5+ years of experience in software engineering, site reliability engineering, quality engineering, infrastructure engineering, or a closely related role in a fast-paced environment.
Demonstrated experience building or operating reliable production software systems, including ownership of testing, observability, deployment confidence, and operational readiness.
Strong technical fluency in modern software architectures, APIs, distributed systems, CI/CD, and cloud or platform infrastructure.
Experience working with frontier AI tooling, AI coding assistants, LLM-enabled applications, or agentic systems, including awareness of the unique 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.
Strong debugging, root cause analysis, and incident response instincts, with a bias toward preventing classes of failures rather than repeatedly reacting to them.
Excellent written and verbal communication skills, with the ability to influence senior engineers and cross-functional stakeholders 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 supporting AI-first or AI-accelerated software development teams, including designing quality controls around non-deterministic system behavior.
Experience with automated testing strategies spanning unit, integration, end-to-end, performance, and reliability testing for complex software products.
Experience with infrastructure as code, cloud platforms, observability stacks, release engineering, and production operations.
Experience in hyper growth startup-like environments, with demonstrated success balancing speed, ambiguity, and engineering rigor.
Familiarity with enterprise systems and business process domains such as ERP, MES, WMS, CRM, finance systems, or manufacturing systems.
Eligible to obtain and maintain a U.S. Secret security clearance.

Highly competitive equity grants
Top-tier benefits for full-time employees supporting health, recovery, and whatever comes next

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