QA Engineer

Konovo is a global healthcare intelligence company on a mission to transform research through technology- enabling faster, better, connected insights.

Konovo provides healthcare organizations with access to over 2 million healthcare professionals and patients, the largest network of its kind globally. With a workforce of over 200 employees across 5 countries: India, Bosnia and Herzegovina, the United Kingdom, Mexico, and the United States, we collaborate to support some of the most prominent names in healthcare. Our customers include over 300 global pharmaceutical companies, medical device manufacturers, research agencies, and consultancy firms.

We are an established but fast-growing business- powered by innovation, data, and technology. Konovo’s capabilities are delivered through our cloud-based platform, enabling customers to collect data from healthcare professionals and transform it into actionable insights using cutting-edge AI in conjunction with proven market research tools and techniques. 

Our Whitefield-based India team is our innovation hub and foundation for scaling product and technology globally. It is also our center of excellence for building scalable platforms, AI-enabled capabilities, and next‑generation healthcare technology. As a Senior Quality Assurance Engineer, you will help shape how quality is engineered across our platform, not just how software is tested. This is a hands-on role for someone who believes quality is built into engineering from day one and thrives on scaling quality through automation, observability, and AI.

How You’ll Make an Impact:

• Define and scale quality engineering standards, quality gates, and release-readiness frameworks across multiple squads.
• Architect end-to-end test strategy covering UI, API, database, integration, security, and performance testing.
• Drive shift-left quality practices across the SDLC; partner with developers to embed quality in PRs and release cycles.
• Implement risk-based testing and prioritization to uncover hidden gaps early and focus effort on the highest-impact areas.
• Design, build, and scale enterprise automation frameworks; expand end-to-end automation for critical business workflows.
• Reduce manual regression through intelligent automation; improve stability, minimize flaky tests, and strengthen CI/CD quality signals.
• Partner with Konovo’s global teams to integrate AI into QE (test generation, defect classification, automated RCA, trend prediction, flaky detection, release health dashboards).
• Define performance benchmarks, identify bottlenecks across services/APIs/data flows, and drive scalability, reliability, and response-time improvements.
• Establish continuous monitoring and observability standards; track pipeline health, failures, and release stability in real time.