Intelligence Engineer: Quality Expert and Outcome Validator

This role is not about writing test cases, executing regression suites, or validating features after the fact.

We are looking for someone who treats quality as a system, not a checklist. Your job is to detect risk early, surface patterns in failures, and help engineering teams prevent issues before they reach production.

If your background is purely manual QA, UAT, or test execution, this role will not be a fit.

What You’ll Actually Do

• Analyze production, staging, and test data to identify quality patterns, anomalies, and early warning signals
• Design quality metrics and indicators that reflect system health, not just pass/fail results
• Investigate recurring defects and failures to identify systemic root causes

Partner closely with engineers to

• validate assumptions
• challenge incomplete fixes
• prevent regressions at the system level
• Build lightweight tooling, queries, or dashboards to make quality visible and actionable

Use data to answer questions like

• “Where are we accumulating hidden risk?”
• “Which parts of the system are becoming fragile?”
• “What is likely to break next, and why?”

What This Role Is Not

• Not a manual QA role
• Not a test execution role
• Not a UAT sign-off role
• Not a checklist or compliance-only QA role

What We’re Looking For

• Strong analytical and systems thinking
• Comfort working with data (queries, logs, metrics, trends)
• Ability to reason about cause and effect in complex systems
• Engineering mindset, even if you’re not a full-time developer
• Willingness to challenge assumptions and ask uncomfortable questions
• Helpful Backgrounds (but not required)
• Software engineering
• Data engineering / analytics
• SRE / production support
• Platform or infrastructure engineering
• Semiconductor, manufacturing, or systems engineering with strong data exposure

Explicit Note

If your primary experience is manual testing, writing test cases, or executing predefined QA scripts, this role is not a match.