AI Evaluation Engineer

Zof AI; San Francisco, Northern (CA, KY); On-site; USD 120,000 - 160,000; Full time

Job summary

Zof AI in San Francisco, CA is seeking an AI Evaluation Engineer to design and build eval suites and verification harnesses for AI products.

You will turn customer requirements into testable checks, investigate failure modes like regressions and hallucinations, and integrate evals into CI. The role emphasizes rigorous measurement, clear communication, and ownership in a fast-moving environment.

Qualifications

• Experience testing, evaluating, or QA-ing complex software systems.
• Understanding of how LLM and agent systems fail.
• Strong analytical rigor and skepticism.
• Ability to write code to build harnesses and automation.
• Attention to detail and a high quality bar.
• Clear written and verbal communication.
• Comfort operating in a fast-moving environment.
• High ownership.

Responsibilities

• Design and build eval suites for AI products and agent systems.
• Build verification harnesses that confirm the AI built the right thing.
• Define quality gates that gate what ships and what does not.
• Turn domain expertise and customer requirements into testable checks.
• Hunt failure modes: regressions, hallucinations, and silent errors.
• Make eval results legible to engineers, product, and customers.
• Wire evals into CI and the development loop.
• Raise the standard for what "working" means across the company.

Skills

QA testing

Evaluation

SQL/Script coding

CI integration

Analytical thinking

Communication

Ownership

Attention to detail

Tools

Test automation tooling

Job description

Zof AI is seeking an AI Evaluation Engineer to build the tests that determine whether AI actually works. Verification is the heart of what Zof AI does, so this role sits close to the core of the product: designing eval suites, verification harnesses, and quality gates that confirm AI systems built the right thing, part QA discipline and part domain judgment. The ideal candidate is skeptical by default, rigorous about measurement, and motivated by turning "it seems to work" into evidence.

Engineering · Mid to Senior · Full-time · On-site · San Francisco, CA

Responsibilities

• Design and build eval suites for AI products and agent systems.
• Build verification harnesses that confirm the AI built the right thing.
• Define quality gates that gate what ships and what does not.
• Turn domain expertise and customer requirements into testable checks.
• Hunt failure modes: regressions, hallucinations, and silent errors.
• Make eval results legible to engineers, product, and customers.
• Wire evals into CI and the development loop.
• Raise the standard for what "working" means across the company.

Requirements

• Experience testing, evaluating, or QA-ing complex software systems.
• Understanding of how LLM and agent systems fail.
• Strong analytical rigor and skepticism.
• Ability to write code to build harnesses and automation.
• Attention to detail and a high quality bar.
• Clear written and verbal communication.
• Comfort operating in a fast-moving environment.
• High ownership.

Nice to have

• Experience building LLM evals, benchmarks, or test infrastructure.
• QA, SDET, or test automation background.
• Domain expertise in a vertical where correctness matters.
• Experience with statistical evaluation methods.

Must understand how to measure whether AI systems actually work, beyond demos