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Lead Performance Test Engineer
Quality Assurance
Bengaluru, Karnataka, India
Posted on Aug 21, 2026
Role Overview
We are seeking an experienced Lead Performance Test Engineer to lead and scale performance engineering practices for our cloud-native SaaS platform. This role is responsible for driving performance, scalability, reliability, and cost efficiency at an organizational level, with a strong focus on serverless and distributed architectures.
You will define performance engineering strategy, build scalable and AI-driven performance platforms, and influence architectural decisions across teams. The role requires deep expertise in modern cloud environments and a strong focus on embedding performance into the entire software lifecycle, from development to production.
Key Responsibilities
- Define and drive organization-wide performance engineering strategy aligned with business KPIs, customer experience, and cost efficiency
- Architect and build scalable, self-service performance engineering platforms enabling teams to run performance tests and analysis independently
- Design and implement AI-driven performance engineering solutions including anomaly detection, predictive performance insights, adaptive load testing, and automated optimization recommendations
- Lead the design and execution of advanced performance testing strategies for serverless, distributed, and event-driven systems
- Establish and standardize performance benchmarks, SLAs, SLOs, and KPIs across services
- Drive integration of performance testing and validation into CI/CD pipelines to enable continuous performance engineering (shift-left approach)
- Analyze system-wide performance bottlenecks including latency, cold starts, concurrency limits, and resource utilization across distributed systems
- Collaborate with engineering, SRE, and architecture teams to influence system design for scalability, resilience, and performance optimization
- Own performance in production environments by leveraging observability tools, distributed tracing, and real-time monitoring systems
- Implement intelligent observability solutions using tools such as CloudWatch, Datadog, New Relic, and AI-based monitoring platforms
- Lead capacity planning and scalability initiatives for high-throughput and globally distributed systems
- Drive cost-performance optimization strategies in cloud-native environments (FinOps alignment)
- Mentor and guide engineers across teams, promoting a performance-first culture and best practices
- Stay updated with emerging trends in performance engineering, including AI/ML-driven optimization and cloud-native innovations
Desired Skills & Requirements
Must Have
- 8+ years of experience in performance engineering in large-scale SaaS or cloud-native environments
- Strong expertise in performance testing tools such as JMeter, Gatling, Locust, or similar
- Deep experience with serverless architectures (AWS Lambda, API Gateway, event-driven systems)
- Hands-on experience with performance monitoring and observability tools (CloudWatch, Datadog, New Relic, distributed tracing systems)
- Experience building performance engineering frameworks or platforms at scale
- Strong understanding of performance characteristics in distributed and serverless systems (latency, cold starts, concurrency, scaling behavior)
- Experience integrating performance engineering into CI/CD pipelines
- Proficiency in programming/scripting (Python, Java, or similar)
- Experience with AI/ML-based performance optimization techniques such as anomaly detection, predictive analysis, or adaptive load modeling
- Strong knowledge of cloud platforms (AWS preferred) and performance optimization techniques
- Proven ability to identify and resolve complex performance bottlenecks
- Experience with large-scale load testing and capacity planning
- Strong understanding of cost-performance trade-offs in cloud environments
Good To Have
- Experience with Kubernetes and containerized environments alongside serverless architectures
- Exposure to chaos engineering and resilience testing practices
- Experience building internal developer platforms or self-service tooling
- Knowledge of FinOps practices and cloud cost optimization strategies
- Experience with globally distributed or multi-region architectures
- Familiarity with API performance optimization techniques
- Experience with modern data stores (DynamoDB, Aurora Serverless, NoSQL systems)
- Exposure to AIOps platforms and intelligent observability systems
Soft Skills
- Strong problem-solving and analytical thinking
- Ability to influence architectural and technical decisions across teams
- Excellent communication and stakeholder management skills
- Ownership mindset with the ability to drive cross-functional initiatives
- Mentorship and leadership capabilities
- Ability to operate in a fast-paced, high-growth SaaS environment
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- Equivalent practical experience in performance engineering or cloud-native systems