Senior Software Development Engineer in Test; SDET

Senior Software Development Engineer in Test (SDET)

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We are looking for a Software Development Engineer in Test (SDET) who thinks beyond individual test cases and cares about systemic quality across teams and services. This role sits at the intersection of QA, Dev Ops, and platform engineering. You will own and evolve our test and QA infrastructure, including designing tools and utilities that the entire QA and engineering organization can use.

You will be a QA evangelist: partnering closely with engineers, QA, and Product to drive best practices in testability, automation, and quality. A key part of the role is to integrate AI into our testing and automation workflows—from intelligent test generation and selection to smarter debugging and triage.

Our platform is well‑established and continues to evolve as we add new features, customers, and workflows. The team is focused on enhancing existing capabilities, consolidating legacy systems into this unified platform, and strengthening automation coverage to improve quality and reliability.

This role is ideal for a high‑energy, proactive engineer who thrives in small, dynamic teams and enjoys taking ownership of problems—designing, developing, and executing QA platform and automation solutions without waiting for step‑by‑step instructions.

• Own and evolve QA/test infrastructure
• Design, develop, and maintain automated test systems for API, service‑level, and integration testing
• Modernize and maintain integration tests and test suites to be faster, more reliable, and easier to extend
• Work closely with Dev Ops/Platform teams to improve test environments, including data setup, configuration, and stability
• Build tools for the QA and engineering org
• Develop reusable frameworks, libraries, CLIs, and dashboards that other QA engineers and developers can leverage
• Implement self‑service utilities that UI and backend teams can reuse for test data, environment validation, and regression checks
• Identify and address automation gaps and QA technical debt, proposing and implementing long‑term solutions
• Integrate AI into the testing process
• Leverage and extend AI‑assisted coding and testing tools to generate tests, prioritize test runs, and assist with debugging and log analysis
• Experiment with and operationalize AI‑driven approaches to test case design, impact analysis, and flakiness detection
• Define guardrails, patterns, and best practices so AI becomes a safe, scalable, and productive part of the QA workflow
• Drive quality practices across teams
• Adopt a BDD‑driven approach for selective, high‑value, business‑readable scenarios that enhance clarity between Product and Engineering
• Advocate for testability and quality during sprint planning, design reviews, and product discussions
• Collaborate with backend and UI engineers to ensure cohesive end‑to‑end testing across services and UIs
• Investigate and debug issues, conduct root cause analysis, and feed learnings back into architecture, tests, and tooling
• Embed with specific product or platform projects over time to design test strategies, coverage plans, and quality gates
• Contribute to code reviews and help shape engineering standards with a quality‑first mindset

• 5+ years in software test engineering, including 3+ years creating and maintaining test automation frameworks for API and DB testing
• Proven strong coding experience in at least one or more programming languages
• Ability to write tests using a BDD framework (e.g., Behave)
• Solid grasp of software engineering fundamentals, design patterns, and best practices
• Hands‑on API testing, contract testing
• CI/CD experience (Jenkins, Git Hub Actions, etc.) and Git best practices
• Comfort with cloud and containers (AWS, Docker) and with databases such as SQL and No
  
  SQL
• Proven analytical and problem‑solving skills with a demonstrated ability to work both independently and in a team environment
• Comfortable working in Agile/Scrum teams, using tools like JIRA and Confluence
• Proficiency in leveraging and evaluating AI‑assisted coding tools (e.g., Git Hub Copilot,…