Lead Quality Assurance Engineer

Overview

Lead the quality engineering function across Konovo's platform, defining how quality is engineered into products from day one rather than only tested after the fact.

What you'll do

• 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 LLM Innovative Technology Team (LITE) 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 and blockers to closure, and provide executive-ready quality metrics, trends, and recommendations.

What you'll need

• 8+ years in software testing/quality engineering, including test automation and/or test architecture, in product environments.
• Proven QA leadership across multiple engineering teams, with strong ownership and clear cross-functional communication.
• Hands-on depth in UI/API automation, integration and 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/Python/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.

Details

• Location: Whitefield, Bengaluru, Karnataka, India.
• Work mode: Hybrid.