Intelligence Engineer: Quality Expert and Outcome Validator at Evismart
Taguig, Metro Manila, Philippines -
Full Time


Start Date

Immediate

Expiry Date

06 May, 26

Salary

0.0

Posted On

05 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Analytical Skills, Systems Thinking, Data Analysis, Cause and Effect Reasoning, Engineering Mindset, Problem Solving, Quality Metrics Design, Defect Investigation, Collaboration, Tooling Development, Data Visualization, Risk Detection, Pattern Recognition, Failure Analysis, Assumption Challenging, Root Cause Analysis

Industry

Software Development

Description
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.
Responsibilities
The role involves analyzing production and test data to identify quality patterns and risks, as well as partnering with engineering teams to prevent issues before they reach production. Additionally, the engineer will design quality metrics and build tools to make quality visible and actionable.
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