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Code Guide

AI Eval Engineer

Emerging

Build and operate the continuous measurement layer that tells the organization whether its AI systems are getting better or worse in production.

Who moves into this role

  • Backend engineer with testing background
  • QA engineer moving into AI
  • ML engineer focused on production reliability

Required skills

Statistical experiment design
Canary pipeline implementation (A/B on 1-2% traffic)
Creator-verifier pattern (+12 to +26% correctness)
OTel GenAI conventions (gen_ai.client stable, gen_ai.agent experimental)

Salary benchmarks (2026)

US market · ±30% · Base only. Europe runs 30–50% lower.

Entry $110K–$150K
Mid-level $150K–$210K
Senior $210K–$290K

Growing rapidly as agentic systems reach production

Frequently asked questions

What does a AI Eval Engineer do?

Build and operate the continuous measurement layer that tells the organization whether its AI systems are getting better or worse in production.

What skills does a AI Eval Engineer need?

The core skills are: Statistical experiment design, Canary pipeline implementation (A/B on 1-2% traffic), Creator-verifier pattern (+12 to +26% correctness), OTel GenAI conventions (gen_ai.client stable, gen_ai.agent experimental).

What is the salary for a AI Eval Engineer in 2026?

In 2026, a AI Eval Engineer earns between $110K–$150K at entry level and $210K–$290K at senior level, with mid-level salaries around $150K–$210K. Growing rapidly as agentic systems reach production. US market figures, ±30%.