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Qa Test Engineer Automation Conversation Quality

💼 Full-time🗓 2026-07-27

Core

Build automated regression systems and test harnesses to ensure conversation quality for AI agents before production release.

Role type

Senior QA Automation Engineer (Conversational AI)

Builds

Automated test suites, conversation test harnesses, release gates

Domain

AI / Conversational Systems / Quality Engineering

Deliverable

production ML models | product features

Required skills

Automated test system design, regression testing, API testing, end-to-end testing, failure mode analysis, test strategy design

Preferred skills

Testing conversational systems, AI/chatbot/voice systems, multilingual behavior testing

Technologies

Automation frameworks

Responsibilities

Build automated regression systems covering conversation flows and edge cases, own conversation test harnesses to simulate real user interactions, reduce production incidents by identifying root causes, define quality standards and benchmarks, collaborate with engineering and product teams to enable fast releases, drive a culture of predictive quality

Seniority

Mid-level, hands-on builder

Rewrite
## About the role Most teams treat QA as the last step. That's why bugs reach production. We are building AI agents where failures are: Visible to customers Hard to debug Expensive to fix This role exists to ensure: Bugs are caught before production Releases are safe and predictable Teams can ship fast without fear ## Responsibilities You will not just test features. You will build the system that guarantees quality. 1. Build an automated regression system Create a test suite that catches 90%+ of conversation quality issues before release Cover: Conversation flows Edge cases Multilingual behavior Ensure regression testing is: Fast Reliable Mandatory before deployment 2. Own conversation test harness Build a system to simulate: Real user conversations Edge cases Failure scenarios Enable teams to: Test workflows quickly Validate changes before release Make daily releases safe and repeatable 3. Reduce production incidents Bring P1 incidents down to <1 per account per month, even at 5x scale Identify: Root causes Recurring failure patterns Ensure issues are fixed permanently, not patched temporarily 4. Define quality standards Establish clear definitions of: What is a bug What is acceptable quality Create: QA benchmarks Release gates Ensure quality is measurable, not subjective 5. Enable fast and safe releases Work closely with: Engineering Product Conversation design Ensure: Testing does not slow down shipping Shipping does not compromise quality 6. Move toward zero-bug production mindset Build systems where: Bugs are rare Failures are predictable Drive a culture where: Quality is owned by everyone QA enables, not blocks ## What success looks like ≥ 90% of bugs caught before production P1 incidents drop to <1 per account per month Teams can ship daily without fear Conversation quality remains consistent at scale Production issues become rare and predictable ## Requirements You have 2–3 years of experience in QA / testing / automation You have built: Automated test systems Regression suites You think in: Systems Failure modes You care about: Quality Reliability Real-world performance ## Nice to have Experience testing: Conversational systems AI / chatbot / voice systems Strong understanding of: Automation frameworks API testing End-to-end testing Ability to: Design test strategies, not just execute them ## What we offer You will define quality standards for an AI platform Your work directly impacts: Customer experience Reliability Product trust You will move the system from: Reactive QA → predictive quality systems ## About the role Not manual testing only Not a release blocker Not reactive bug reporting ## What this role is A builder of quality systems A guardian of production reliability A multiplier of engineering confidence ## One question to self-evaluate Can you build a testing system where bugs are caught before users ever see them?
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