Performance QA Lead Mandatory Skills • 10+ years of experience in performance testing and engineering • Strong hands-on expertise in LoadRunner (or equivalent enterprise performance tools) • Solid experience working with Google Cloud Platform (GCP): o Understanding of cloud architecture, scalability, and performance tuning o Services like GKE, Cloud Run, Compute Engine, Pub/Sub, etc. • Deep understanding of: o Workload modeling o Performance tuning (app, DB, infra) o APM tools (Dynatrace, AppDynamics, Stackdriver, etc.) • Experience integrating performance testing into CI/CD pipelines • Strong scripting and analysis skills • Exposure to AI/ML in performance testing: o Predictive analytics, anomaly detection, intelligent workload modeling ________________________________________ Leadership & Client-Facing Expectations • Highly vocal, articulate, and confident communicator • Proven ability to lead performance war rooms and critical incident discussions • Strong experience in client-facing roles, handling escalations and performance reviews • Ability to challenge assumptions and drive data-driven decisions • Demonstrated ability to drive teams, influence stakeholders, and ensure accountability ________________________________________ Nice-to-Have Skills • Experience with JMeter, Gatling, or k6 • Knowledge of containerization (Docker, Kubernetes) • Experience with observability & monitoring tools in GCP ecosystem • Exposure to AI-powered testing tools/platforms • Domain experience in healthcare or enterprise SaaS platforms ________________________________________ Preferred Qualifications • Bachelor’s/Master’s degree in Computer Science or related field • Experience leading distributed/onshore-offshore teams • Strong understanding of modern SDLC and Agile methodologies L4 – L7 (Tech Lead Architect Principal) Proven experience architecting and delivering systems using agentic IDEs Ability to: • Define architectural intent that agents can follow • Break features into agent executable tasks • Govern AI autonomy (guardrails, permissions, reviews) • Integrate agentic workflows into CI/CD pipelines Experience supervising AI agents across: • Multi service systems • Legacy modernization • Large codebases / monorepos Strong understanding of: • Security implications of autonomous code execution • Compliance, auditability, and traceability • AI assisted SDLC operating models Core Responsibility: • Guide effective use of agentic IDEs for complex, multi-module or cross-service changes • Establish review practices and quality checks for AI-generated code • Mentor team members on balancing autonomy, correctness, and maintainability in AI-assisted development • Design system architectures that support AI-augmented and agentic development workflows • Define guardrails, standards, and governance for the use of autonomous coding agents • Evaluate impact of agentic IDEs on SDLC, CI/CD pipelines, security posture, and technical debt
Compensation range: $ 90,000.00 to 100,000.00 per year
