QA Lead / Quality Engineering Lead - AI-Native Quality Systems

We're building multiple products across the clinical workflow — from AI-driven evaluations to care coordination — and moving fast. This is a startup, not a department.

Read this carefully. If you're a manual tester looking for a comfortable QA role, stop here.

We're building AI-powered clinical software, and our quality function needs to operate at the same level of intelligence and autonomy as the products it tests. We don't need someone who writes test cases from Jira tickets. We need someone who designs quality systems.

Our QA function is ready to scale from strong foundations to systematic automation. You'll be the person who architects that scaling — building the test infrastructure, automation frameworks, and AI-augmented QA workflows that let quality grow without linear headcount.

The person we're looking for has probably managed a team of 3-8 QA testers at some point and had this thought: "Half this team could be replaced by good automation and smart test design." You're tired of babysitting manual testers. You want to build the machine instead of being the machine.

We're paying significantly above market for QA in India because we're not hiring a typical QA person. We're hiring someone who thinks about quality the way a systems architect thinks about infrastructure.

- Architect test automation from zero — Playwright-based E2E, API, and integration test suites across multiple healthcare products

- Build AI-augmented QA — use Claude, Copilot, and AI tools to generate test cases, identify edge cases, and create self-healing test suites

- Integrate QA into AI-assisted development workflows — shift-left testing that catches defects at the source, not the gate

- Own the quality gate — if you don't trust it, it doesn't ship. You have release authority.

- Design regression automation that maintains coverage as multiple products evolve simultaneously

- Establish quality engineering culture — documentation, runbooks, test plans that aren't in anyone's head

Week 1-2: Audit all products. Map coverage gaps. Identify the highest regression risks. Pair with the current QA team to absorb domain knowledge and institutional context.

Month 1: Build the Playwright automation scaffold — CI-integrated, parallel execution, covering critical paths. Establish the QA runbook: how we test, when we test, what blocks a release.

Month 2-3: Attach AI-driven test generation to the framework. Build autonomous QA loops that feed back into development. Get to the point where coverage grows without linear human effort.

Ongoing: Own quality across everything. Context-switch between products in the same week. Pair with engineering on testability. Work directly with the founder and clinical team on healthcare-specific edge cases — billing, HIPAA compliance, clinical workflow validation.

1. Test Automation Architecture — Playwright (preferred) or Cypress E2E suites. API test automation (REST Assured, Postman-based, or custom). CI/CD pipeline integration. Parallel execution. Containerized test environments. Custom reporters.

2. Regression Automation — Systematic regression suites, versioned and updated every sprint. Not a spreadsheet. Not tribal knowledge. A living, automated safety net.

3. AI-Augmented Quality Engineering — Using AI tools to generate tests, create test data, identify edge cases from specs, and accelerate coverage. We're an AI-native company — our QA function must be AI-native too.

4. Healthcare Quality Assurance — HIPAA compliance testing, clinical workflow validation, medical billing edge cases, patient data privacy verification, audit trail testing.

5. Cross-Product Quality Ownership — Multiple healthcare SaaS products. One quality brain.

6. Release Certification — You define "release-ready." You block releases when quality is insufficient — with evidence. You raise risks early, clearly, and decisively.

You think of QA as a system design problem, not a checklist.

You're excited by autonomous testing systems, AI-driven exploration, and replacing manual effort with intelligence. You design feedback loops, not just test suites.

You're uncomfortable with manually writing hundreds of brittle test cases, QA that reacts instead of anticipates, and automation that breaks every sprint.

You communicate like an engineer. Your bug reports tell a story: what happened, why it matters, how to reproduce, what the business impact is. Developers thank you for your bugs.

You've blocked releases before and you'd do it again. Quality isn't negotiable.

You don't wait to be asked. When you see a quality risk forming — in a spec, in a sprint, in a deployment — you surface it. Proactively. Loudly if needed.

You use AI tools in your daily work already. If you haven't figured out how Claude, ChatGPT, or Copilot accelerates quality engineering by now, you're behind.

Evening IST hours with 4–8 hours of overlap to US Pacific (9am–5pm PT). You propose the schedule that works for you — we care about overlap, not clock-in time. Flexibility for critical releases or incident response.

4-8 years of experience in QA, SDET, or Quality Engineering, including a minimum of 2 years in roles such as QA Lead, QA Manager, SDET Lead, or Senior Quality Engineer, responsible for test strategy beyond mere execution.

Test automation architecture—experience in designing and building test frameworks from the ground up rather than merely writing scripts within existing frameworks.

Skilled in Playwright, Cypress, or Selenium—maintained advanced, production-level end-to-end test suites for over 2 years.

API testing—proficient in automated REST API testing using tools such as REST Assured, Postman automation, or custom solutions. Capable of creating programmatic test suites that include authentication, error handling, and edge case coverage.

JavaScript or TypeScript—ability to write, debug, and review test automation code competently.

Git—familiarity with branching, pull requests, and conducting code reviews for test scripts.

Test planning & strategy—capable of developing test plans based on product requirements, prioritizing them by business risk, and knowing what not to test.

Docker/containerized test environments—ability to set up and maintain isolated test infrastructure.

Strong proficiency in English communication—focus on asynchronous communication with clear written bug reports, test documentation, and release readiness notifications, while proactively identifying risks.

- Proven ability to architect test automation frameworks from scratch (e.g., Playwright for E2E, API, and integration tests)

- Experience with AI-augmented QA tools (e.g., Claude, Copilot) to generate test cases and identify edge cases

- Ability to build self-healing test infrastructure and automate workflows to scale quality without linear headcount

- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience)