Lead our global performance engineering organization to drive strategy, execution, and innovation in performance testing, benchmarking, capacity planning, and system optimization for large-scale, distributed cloud platforms to ensure products meet and exceed customer expectations for speed, scalability, resiliency, and efficiency.
Requirements
- Strong expertise in distributed systems, microservices, cloud platforms (AWS, Azure, GCP), and container technologies (Kubernetes, Docker).
- Proficiency in performance tools and frameworks (e.g., JMeter, Gatling, Locust, k6, LoadRunner, custom frameworks).
- Deep understanding of system profiling, database tuning, caching, and network optimization.
- Experience introducing innovative approaches (e.g., ML/AI-driven performance analysis, chaos engineering).
Responsibilities
- Oversee the design and development of performance test frameworks, automation tools, and simulation environments for end-to-end system testing.
- Drive benchmarking and profiling of distributed systems under realistic load and stress scenarios.
- Collaborate with engineering and architecture teams to identify bottlenecks and provide tuning recommendations for backend, frontend, APIs, databases, and infrastructure.
- Ensure performance engineering is integrated early in the SDLC (“shift-left” approach).
- Partner with product management and architects to define scalability goals and capacity models.
- Work with DevOps/SRE to ensure production readiness, observability, and monitoring align with performance standards.
- Introduce AI-driven performance insights, predictive modeling, and automated anomaly detection.
Other
- Define and execute the performance engineering strategy across products, platforms, and services.
- Establish key performance metrics, SLAs, and success criteria aligned with customer and business needs.
- Build and scale a global team of performance engineers, fostering innovation, accountability, and excellence.
- Provide leadership in incident investigations involving performance and scalability issues in production.
- Champion performance best practices, methodologies, and metrics across the organization.
