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