Description
As a Senior Quality Engineer, Applied AI, you will act as the quality and reliability lead within a small, senior AI development pod focused on solving novel, high-impact business and engineering problems.
Your responsibilities will include designing and implementing test strategies, validation approaches, and release readiness criteria for AI-enabled software, automation, and agentic workflows. You will partner closely with software and AI engineers to identify failure modes early across code, prompts, models, integrations, infrastructure, and user workflows.
You will build confidence in fast-moving solutions through automated testing, observability, instrumentation, environment design, and operational safeguards. You will help define practical standards for reliability, resiliency, debugging, and production operations in an AI-first development model.
You will contribute directly in code, infrastructure, and tooling where needed to improve delivery confidence, developer feedback loops, and production stability. You will support launch readiness, production issue response, root cause analysis, and continuous improvement for front-facing systems delivered by the pod.
You will evangelize strong engineering discipline in areas such as quality assurance, release engineering, infrastructure hygiene, and incident prevention without sacrificing speed.
This role requires 5+ years of experience in software engineering, site reliability engineering, quality engineering, infrastructure engineering, or a closely related role in a fast-paced environment.
The ideal candidate will have demonstrated experience building or operating reliable production software systems, including ownership of testing, observability, deployment confidence, and operational readiness.
They will have 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, is highly desirable.
The successful candidate will have excellent written and verbal communication skills, with the ability to influence senior engineers and cross-functional stakeholders on quality and reliability trade-offs.
A degree in Computer Science, Information Systems, Engineering, or related technical field, or equivalent practical experience, is required.
U.S. Person status is required as this position needs to access export-controlled data.
Eligibility to obtain and maintain a U.S. Secret security clearance is also preferred.