AI-Native Software Engineer, QA Automation

• Build and maintain the QA automation harness across browser, API, data, and workflow layers
• Create automated checks that run on every meaningful change
• Build synthetic test data and isolated test environments
• Own the UAT/QA automation pipeline from requirement to test plan to run to evidence
• Use AI agents to generate, execute, improve, and debug tests
• Build independent agent-driven QA workflows that test the work of code-writing agents
• Prove tests work by reintroducing known bugs and showing they fail correctly
• Reduce flaky tests and distinguish real product failures from environment noise
• Produce reliable QA evidence for releases
• Work with engineering and product to define quality gates for critical user journeys
• Help design and operate browser/API test runners, synthetic data systems, isolated environments, requirement-to-test workflows, automated checks, agent-driven QA workflows, evidence generation, failure routing, and quality metrics
• Map the current QA setup and highest-risk user journeys during the first 30 days
• Deliver an automated end-to-end QA lane that runs on every change and catches a known bug within the first 30 days
• Ensure key Assess and Zenflow journeys are automatically covered and every release has QA evidence within the first 90 days
• Measure and improve flaky-test rate and runtime

• Mid to senior-level software engineering ability
• Ability to design, write, debug, and maintain code
• Experience with test automation using Playwright, Cypress, API testing frameworks, or similar tools
• CI/CD experience and comfort wiring tests into build and release workflows
• Practical experience using AI agents to create or improve tests
• Strong judgment about whether a test actually proves anything
• Ability to seed a bug, run a test, and demonstrate that the test catches the failure
• Comfort debugging flaky tests, environment issues, and test data problems
• Skeptical, evidence-driven thinking
• Clear communication around risk, coverage, and release confidence
• Ability to use agents to generate test ideas, test code, and edge cases
• Ability to critically review agent-created tests
• Ability to build workflows where agents test independently from code-writing agents
• Ability to use AI to analyze failures and propose debugging paths
• Ability to create repeatable quality gates that scale with development speed
• Ability to measure whether AI-generated tests are useful
• Ability to avoid false confidence from tests that pass without proving behavior
• Healthcare or regulated-software experience is a nice to have
• Experience testing AI-powered features is a nice to have
• Experience building test environments and synthetic data is a nice to have
• Performance or load testing experience is a nice to have
• Attendance required during approximately 6:00 PM–12:00 AM IST for meetings and live collaboration
• Approximately 50 hours per week commitment

• Fully remote work
• Equipment allowance
• Direct access to the founder and Head of Engineering
• Opportunity to build the QA function as an engineering platform from the ground up
• Competitive compensation, based on demonstrated ability and experience