Senior Test Automation Engineer

present of AI; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Rad AI seeks a senior test automation engineer to define the testing strategy for a product area in generative AI software for radiology. You will build and maintain automation frameworks that other engineers rely on and clearly communicate release risk to the team.

We emphasize hands-on automation, prudent testing scope, and shifting the team from finding defects late to preventing them early. This role focuses on AI output and clinical text where accuracy matters, offering growth in an

Qualifications

• Experience in test automation strategy and framework development.
• Ability to assess release risk and prioritize checks.
• Hands-on automation engineering with quality-focused mindset.

Responsibilities

• Define testing strategy for a product area in generative AI.
• Build and maintain automation frameworks used by the team.
• Design checks for AI output where accuracy matters (radiology context).
• Evaluate risk and help prevent defects early in the release cycle.

Job description

A senior test automation engineer is usually expected to set the testing strategy for a product area, build and maintain automation frameworks other engineers rely on, and make release risk clear to the team. A strong candidate brings deep hands on automation work, sound judgment about what to test and what to skip, and the ability to shift a team from finding defects late to preventing them early. At a company building generative AI software for radiology, that means testing carefully around clinical text and report output where accuracy matters.

How it fits the AI era

AI tools can draft test cases, generate scripts and flag likely breakages, which speeds up routine automation work. What stays human is deciding what correctness means for a product that drafts medical report impressions, judging risk, and designing checks for AI output that is not fully predictable. The role leans more toward strategy and prevention than toward writing every test by hand.

How it builds AI experience

Working here would build experience testing generative AI output, such as checking drafted report impressions and follow up tracking for consistency and safety. That experience comes from designing evaluation checks for model driven features, not only from using AI coding assistants. Building a small project that tests an AI text generator against expected outputs would be a practical way to prepare.

Worth showing

• Release risk assessment
• Testing AI generated output

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Rad AI

Rad AI builds generative AI software for radiology that drafts report impressions, speeds up reporting, and tracks follow-up on incidental findings, per the company.