Senior QA Engineer (AI-Driven)

Position Overview

We are looking for a Senior QA Engineer who understands that AI-generated code is not tested code — and that a passing test suite doesn't mean a working product.

At Productera, QA is not a checkbox at the end of the sprint. It's a core part of how we ship. You will work inside lean, AI-assisted engineering teams — and your role is to be the person who thinks not from the spec, but from the user and what they actually do.

Real users don't follow the happy path. They skip steps, refresh mid-flow, send unexpected inputs, open two tabs, lose connection, and come back later. Your test strategy starts there — not with what the documentation says should happen, but with what a real person will eventually do.

On top of that, AI writes plausible code. You'll find the places where plausible isn't correct: race conditions in payment retries, idempotency violations, broken auth flows, and edge cases the model never considered — including the ones where the code looks right but behaves wrong under real conditions.

This is a senior role. You will own QA strategy from the ground up — not execute someone else's test plan.

Key Responsibilities

• Design and own end-to-end QA strategy built around user behavior, not documentation — from test planning through release. Build and maintain automated test suites covering functional, regression, and integration layers — with human review of any AI-generated test cases.
• Run full-path integration tests and fuzz testing to catch correct-looking-but-wrong logic that passes basic checks but breaks under real conditions.
• Conduct security-focused exploratory testing: IDOR vulnerabilities, authentication bypass, input validation gaps, session management flaws, and exposed endpoints.
• Identify and document the systematic failure patterns of AI-generated code — not just individual bugs, but categories of risk that emerge from how LLMs generate logic.
• Audit features the way an external reviewer would: assume nothing works as documented until proven otherwise.
• Collaborate with architects and engineers to identify quality and security risks before they reach production.
• Define acceptance criteria together with Tech PMs that go beyond "it works" — including edge case handling, failure modes, and how the system behaves when users do the unexpected.
• Support teams working in regulated industries (fintech, healthtech, insurtech) with testing practices aligned to compliance requirements (SOC 2, HIPAA, ISO 27001).

Requirements

• Proven experience as a Senior QA Engineer in production software environments — owning quality strategy, not executing test plans.
• Deep expertise in test automation: building and maintaining frameworks, not just writing scripts. Critically: knowing when AI-generated test cases need to be supplemented or overridden by human judgment.
• User-behavior-first thinking: ability to design test strategies from real usage patterns — what users actually do, not what they're supposed to do.
• Strong security testing mindset: ability to identify authentication issues, authorization gaps, injection vectors, and infrastructure exposure.
• Experience testing API-based and distributed systems, including async flows, event-driven architectures, and third-party integrations.
• Familiarity with fuzz testing, regression suites for known AI failure patterns, and full-path integration testing.
• Comfort working in environments where AI tools are used to generate both code and tests — and understanding what that means for coverage, trust, and risk.
• Experience in regulated or high-stakes domains (financial transactions, healthcare data, user authentication). Fluent English (spoken and written).

Preferred Qualifications

• Hands-on experience testing AI-generated or LLM-assisted codebases, with awareness of their specific failure patterns.
• Background in security testing or penetration testing — formal or self-developed.
• Familiarity with compliance frameworks: SOC 2, HIPAA, ISO 27001, or PCI DSS.
• Experience working inside lean, fast-moving engineering teams where QA must scale without headcount.
• Exposure to observability and monitoring tools — understanding that production QA doesn't stop at release.
• Experience defining quality gates in CI/CD pipelines.

We Offer

• Compensation in USD.
• Remote work with flexible schedule. We respect your life and work style. We don't care if you are an early bird or night owl — we value timely and quality results more than the time of the day the work is being done.
• Work on cutting-edge AI product development, where QA is a first-class engineering discipline, not an afterthought.
• A team that understands the difference between cognitive debt and technical debt — and cares about both.