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Senior QA Engineer

Open 30d

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, 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.
  • Own end-to-end QA delivery across global teams -drive risks/blockers to closure and provide executive-ready quality metrics, trends, and recommendations.

What We’re Looking For:

  • 6+ years in software testing/quality engineering, including test automation and/or test architecture, in product environments.
  • Strong ownership and clear cross-functional communication.
  • Hands-on depth in UI/API automation, integration & database testing, performance testing, and building test frameworks.
  • Strong CI/CD quality engineering and observability exposure (e.g., Jenkins/GitHub Actions, Grafana) plus cloud familiarity (AWS/Azure/GCP).
  • Proficient in Java/JavaScript (or similar) and modern automation tooling (e.g., Playwright/Cypress, K6, JMeter, Agentic AI, MCP servers).
  • Mentor and grow engineers through clear feedback and hands-on support.
  • Operate effectively in ambiguous, global, fast-moving environments.
  • Apply and experiment with AI-enhanced engineering workflows with strong judgment and responsibility.

Why Join Konovo?

  • Be part of a mission-driven organisation that is empowering life science researchers and data scientists with the broadest ecosystem of healthcare audiences and an intelligent, AI-enabled platform — so insights aren't just collected, they're connected.
  • Join a fast-growing global team with opportunities for professional growth and advancement.
  • Build technology that enables faster, smarter healthcare research and improves global patient outcomes.
  • Enjoy a collaborative and hybrid work environment that fosters innovation and flexibility.
  • Experience a workplace that puts employees first, offering a workplace designed for growth, well-being, and balance.
  • Become a part of an organisation that prioritizes your well-being with comprehensive benefits, including group medical coverage, accident insurance, and a robust leave policy. Our employee-centric policies ensure a rewarding and fulfilling work experience.
  • Make a real-world impact by helping healthcare organisations innovate faster.

If you’re eager to build a meaningful career in healthcare market research and you’re smart, nice, and driven to make an impact we’d love to hear from you!

Apply now to be part of our journey.

What this application asks

greenhouse

First Name, Last Name, Email, Phone, Resume/CV, Cover Letter

  • Preferred First Name optional
  • LinkedIn Profile
  • Website optional
  • How did you hear about this job?
  • Are you comfortable working in a hybrid mode, 3 days a week, from our Whitefield, Bengaluru office? choose one
  • How many years of hands-on experience do you have building, scaling, and operating automation frameworks or quality engineering systems in production environments? choose one
  • Which distributed system testing patterns have you personally validated or automated in production systems? choose any
  • Which AI-powered engineering tools or workflows have you used in production or day-to-day quality engineering? choose one
  • Which cloud platforms have you used for test automation, deployment validation, performance testing, or production monitoring? choose any
  • Which option best reflects your experience taking ownership of complex technical or operational challenges? choose one
  • A P0 incident happens after a release: a customer-facing survey feature is silently dropping ~8% of submitted responses, even though the regression suite passed and QA signed off. In 6–10 bullets, walk us through: What you do in the first 30 minutes (checks, who you involve, what you communicate) How you help drive root cause analysis, even if the defect is in backend/infra What likely gaps in the quality approach allowed this to slip, and what you’d change to prevent it (beyond “add a test”) What QE commitments you would own coming out of the post-mortem (process, automation, monitoring/alerts, release gates) written answer
  • You've joined a squad building a new healthcare data ingestion API that processes ~500K survey responses/day from external panel providers. The API has 12 endpoints (mix of REST and async event-driven), 3 downstream integrations (Kafka, Snowflake, and an internal ML service), and PII flowing through it (obfuscation required in lower environments). There is a hard SLA of <200ms p95 latency and 99.95% uptime. There is no existing automation and the team ships every 2 weeks. Please describe your end-to-end test strategy (functional, contract, integration, performance, security), including what you’d build first vs. later; how you’d handle test data management given PII constraints; how you’d validate async/event-driven flows (Kafka consumers, eventual consistency); what tools/libraries you’d choose and why (be opinionated); and how you’d integrate this into CI/CD so failures block bad releases without slowing developers down. written answer
  • What is your notice period (in days)?
  • What is your current CTC? (Fixed + Variable)
  • What is your expected CTC?
  • Are you currently legally authorized to work in the country in which this job is based (e.g. you are a citizen, you have a visa, etc.)? choose one
  • Processing of Personal Data* choose any

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