QA Automation Lead (Performance Testing)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a QA Automation Lead (Performance Testing) in India.

This role is a senior technical leadership opportunity focused on defining and driving performance engineering strategy for large-scale, high-growth systems. You will ensure that complex web and backend platforms are resilient, scalable, and capable of handling peak traffic and hyper-growth scenarios. Acting as a key quality advocate, you will work closely with engineering, DevOps, and SRE teams to embed performance testing early in the development lifecycle. The role combines hands-on test design and automation with strategic ownership of performance standards, SLAs, and CI/CD integration. You will leverage modern tools, cloud infrastructure, and AI-driven approaches to model real-world usage and identify bottlenecks before production impact. This is a highly impactful position for someone passionate about building reliable, high-performance systems at scale.

• Define and lead the performance testing and performance engineering strategy, ensuring systems are scalable, reliable, and optimized for high-traffic usage scenarios.
• Design, develop, and execute performance, load, stress, and endurance tests for web applications, APIs, and backend services, ensuring early identification of performance risks.
• Analyze system behavior under load to identify bottlenecks across application code, APIs, databases, infrastructure, and third-party services.
• Build and maintain performance automation frameworks using Python and tools such as Locust, integrating AI-driven approaches to generate realistic traffic models and test scenarios.
• Integrate performance testing into CI/CD pipelines, establishing automated performance gates to prevent regressions from reaching production.
• Collaborate with engineering, DevOps, SRE, and product teams to define performance benchmarks, SLAs, capacity planning, and scalability requirements.
• Produce clear performance reports and dashboards with actionable insights, trends, and recommendations for optimization and system improvements.
• Drive adoption of performance engineering best practices and promote a “shift-left” approach within the SDLC.

Requirements

• 7–10 years of experience in software quality assurance, including at least 5 years specializing in performance, load, stress, and scalability testing.
• Strong hands-on experience designing performance testing strategies for distributed systems, web applications, and APIs.
• Advanced proficiency in Python for building scalable and maintainable test automation frameworks.
• Experience with performance testing tools such as Locust, JMeter, Gatling, or similar tools.
• Strong understanding of performance metrics including latency, throughput, response time, error rates, and system resource utilization.
• Experience working with CI/CD pipelines and implementing automated performance gates and regression detection.
• Hands-on experience with AWS infrastructure, containerized environments, and modern cloud-native architectures.
• Experience with observability and APM tools such as Datadog, New Relic, or Dynatrace for root cause analysis.
• Strong analytical, debugging, and problem-solving skills with the ability to interpret complex system behavior.
• Excellent communication skills to translate technical findings into clear insights for both technical and non-technical stakeholders.
• Exposure to AI-driven testing approaches, including LLM validation, prompt testing, and AI-assisted automation (strong plus).

Benefits

• Fully remote work environment with global team collaboration
• Competitive compensation aligned with experience and expertise
• Opportunity to work on large-scale, high-performance distributed systems
• Strong emphasis on learning, innovation, and modern engineering practices
• Exposure to advanced AI-driven QA and performance engineering practices
• Collaborative, engineering-driven culture with high autonomy
• Career growth opportunities in a fast-scaling global technology environment
• Access to modern cloud, observability, and automation toolsets