Job Description

We are seeking an experienced Lead QA / Test Automation Engineer to join our Inference team at Firebird AI. The ideal candidate owns quality from test strategy to the release decision, combining strong QA fundamentals with hands-on automation skills. This is a role for engineers who look beyond the API response, verify data exactly across services, queues and storage, and set the standard for how the team tests.

Responsibilities:
  • Define the QA strategy for backend services and APIs, and write test plans for releases and features
  • Build and maintain test automation for APIs and multi-service flows, including test data as code
  • Run structured and exploratory testing, and decide what to automate and what to keep manual
  • Verify system state beyond the HTTP response across databases, message queues and caches
  • Test authenticated flows end to end, including OAuth2/OIDC, API keys and token lifecycle
  • Investigate failures in Kubernetes and separate environment issues from product defects
  • Own defect reporting and release gating with clear reproductions and pass/fail criteria
  • Set QA standards, review tests and mentor engineers on testing practices
  • Collaborate with engineering and product teams to build quality in from the start
Required Qualifications:
  • 7+ years in software quality assurance, including test automation for backend systems and APIs
  • Experience owning QA for a product or team, such as setting standards, reviewing tests or mentoring other engineers
  • Solid QA fundamentals: test levels and types, risk-based prioritisation, equivalence and boundary analysis, traceability from requirements to test cases, and the defect lifecycle
  • Experience writing test strategies and test plans for a release or feature, with defined scope, entry and exit criteria, coverage and acceptance criteria
  • Strong manual and exploratory testing skills, and good judgement on what to automate versus keep manual
  • Ability to verify system state beyond the HTTP response using SQL, message-queue inspection and cache inspection
  • Experience managing test data as code: fixtures, seeding and environment reset
  • Experience testing authenticated flows: OAuth2 and OIDC, API keys, token expiry and revocation
  • Working knowledge of Kubernetes for testing: reading logs, port-forwarding, running test jobs and separating environment issues from product defects
  • Experience with end-to-end testing of multi-service flows where data (amounts, counts, statuses) must be asserted exactly
  • Clear defect reporting with reproductions and pass/fail criteria, and experience with release gating
Nice To Have:
  • API testing from an OpenAPI contract: positive and negative cases, error handling, pagination, idempotency and streaming responses
  • Browser end-to-end automation with Playwright or Cypress
  • Performance and load testing (JMeter, AIPerf or similar) and interpreting latency and throughput results
  • Resilience and failure-mode testing: service restarts, message redelivery, dependency outages and recovery procedures
  • Wiring test suites into CI/CD pipelines (GitHub Actions or similar)
  • Basic security testing: input validation and authorization boundaries
  • Experience with quality or regression evaluation
  • Familiarity with LLM or OpenAI-compatible APIs
Skills:
  • QA fundamentals
  • Test automation
  • Manual and exploratory testing
  • Test strategy and planning
  • Defect reporting
Technologies:
  • Kubernetes
  • SQL
  • Playwright
  • Cypress
  • JMeter
  • GitHub Actions
  • OAuth2
  • OIDC
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