The opportunity

Our core mission is to enhance the performance and reliability of our distributed microservices platform, which operates across AWS, Azure, and GCP and powers large-scale, user-facing applications.

We are expanding our Performance Engineering team and seeking motivated engineers. You will be expected to drive significant, measurable improvements in system performance and reliability, while also setting and upholding a higher performance standard across all our engineering teams.

Problem we are solving now:

• Driving Performance Ownership: Influence and guide engineering teams (squads) to integrate performance considerations into their daily workflows and prioritization, fostering a culture of performance ownership.
• Leading Performance Initiatives: Spearhead performance-focused projects that cover the entire Software Development Life Cycle (SDLC), from conception through deployment.
• Performance Bottleneck Resolution: Collaborate closely with various engineering teams and domains to pinpoint and eliminate performance bottlenecks across all services.

What you'll own

• Lead deep-dive performance investigations on critical services using metrics, logs, traces, and load testing
• Design and execute  performance tests across, multi-cloud microservices environment
• Define performance baselines and non-functional requirem

What you bring

• 6 –10 years of performance engineering experience across large-scale distributed systems
• Strong hands-on experience with load testing tools — k6, Gatling, JMeter, or equivalent
• Deep proficiency with Grafana, Prometheus, and distributed tracing — query writing, alerting, and interpreting graphs
• Hands-on experience with Kubernetes, including resource management and scaling behaviour
• Practical experience across at least two of AWS, Azure, or GCP — and how cloud-specific behaviour affects system performance
• Ability to diagnose complex performance issues end-to-end — latency, throughput, resource saturation, inter-service dependencies
• Experience designing and executing performance tests in live or production-constrained environments
• Solid experience with CI/CD pipelines and Git-based workflows — including integrating performance tests into build and deployment stages
• Strong automation mindset — scripting, tooling, and building frameworks that scale beyond manual execution
• Ability to convert technical findings into clear, actionable recommendations for both engineering and product audiences
• Proven ability to influence engineering teams and drive performance improvements without direct authority
• Prior experience establishing or evolving a performance engineering practice within an engineering organisation

Good to have

• Profiling experience across JVM, Go, or Python
• Exposure to chaos engineering principles and tooling
• Experience defining non-functional requirements from scratch with product and architecture teams
• Exposure to AI-assisted engineering tools — Cursor, Claude, Copilot, or similar — and an appetite for applying them to automate performance workflows