Staff Software Engineer

Zendesk Zendesk · Enterprise · Singapore

Staff Software Engineer focused on Engineering Productivity Test team, building AI-powered tooling and services to improve software testing, validation, and release processes for Zendesk engineers. The role involves owning core testing services, creating automation, and partnering with product teams to enhance developer experience and quality at scale.

What you'd actually do

  1. Build and evolve AI-powered capabilities that improve testing productivity and software quality across Zendesk.
  2. Own and evolve the core testing services, tools, and frameworks that engineers rely on to ship with confidence.
  3. Create automation and infrastructure that makes the testing ecosystem fast, reliable, and developer-friendly, continuously reducing friction in the delivery pipeline.
  4. Partner closely with product and platform engineers to understand pain points, prioritize the highest-impact improvements, and drive adoption through great ergonomics.
  5. Be the go-to engineer for testing productivity: respond to requests, troubleshoot issues, and turn feedback into scalable improvements.

Skills

Required

  • Strong software engineering fundamentals (APIs, debugging, code quality, performance-minded development)
  • Experience building, maintaining, or operating test platforms and tooling (services, frameworks, CI/CD integrations) that enable QA and engineering teams
  • Familiarity with end-to-end testing ecosystems and common tools (e.g., Playwright, Cypress, Selenium, or similar)—focused on enablement rather than authoring tests
  • Proven ability to improve reliability and developer experience in testing workflows (reducing flakiness, improving stability, speeding up feedback loops)
  • Proficiency in one or more languages used for internal tooling (e.g., Ruby, Go, TypeScript/JavaScript, Python)
  • Solid understanding of CI/CD pipelines and how test stages run at scale in build systems (e.g., GitHub Actions, Jenkins, or similar)
  • Strong troubleshooting skills across systems and environments (pipelines, dependencies, infrastructure, test environments) with a systematic approach
  • A strong “internal customer” mindset: comfortable handling requests from QA and engineers, prioritizing effectively, and communicating clearly
  • Strong collaboration skills across teams and time zones; able to drive adoption and influence without direct authority

Nice to have

  • Interest and ability to apply AI/LLM-assisted approaches to improve testing productivity and software quality
  • experience with observability (logs/metrics/traces) and using data to measure reliability and productivity improvements
  • experience operating internal services (on-call rotations, incident response, SLOs) and improving operational readiness

What the JD emphasized

  • AI-powered capabilities
  • testing productivity
  • software quality
  • developer experience
  • AI/LLM-assisted approaches

Other signals

  • AI-powered capabilities
  • testing productivity
  • software quality
  • developer experience