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SKILL_PATH // QA / EVAL ENGINEER

Test AI systems. The #1 most in-demand skill.

Your QA instincts already transfer. The gap is shorter than you think.

Evaluation is the single most frequently cited skill in AI job postings. QA engineers already think in test cases, edge cases, and regression. You already know how to define "correct." You just need to learn how to define it for probabilistic systems.

WHERE THIS ROLE EXISTS
Amazon
QA for AI features, eval pipeline owner
ServiceNow
Quality engineering for AI platform
Any company
The person who proves the AI actually works
YOUR PRIORITY SKILLS

Your target skill profile — what to learn and how deep to go.

1

Eval Frameworks

Expert

Building evaluation suites that actually measure what matters

2

LLM-as-Judge

Expert

Automated evaluation at scale — rubric design, calibration, bias detection

3

Regression Detection

Expert

Catching quality drops from model updates, prompt changes, provider switches

4

Red-Teaming

Proficient

Security testing for LLMs — jailbreaks, injection, data leakage

5

Failure Modes

Proficient

AI fails differently from software — probabilistic, not deterministic

60-DAY MILESTONE

Build an eval harness for an existing AI feature — dataset, metrics, CI integration, regression alerts.

2-YEAR DESTINATION

AI Quality Lead / Eval Engineering Manager

$150–350K

"QA engineers have the shortest gap to the single most in-demand AI skill."

Start your diagnostic →

Free. 3 questions. Personalized skill sequence in 3 minutes.

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