This role is a unique opportunity to combine technical leadership, hands-on optimization, and cross-team collaboration, ensuring performance best practices are embedded across the development lifecycle.
As a Performance Tech Lead, you will define and implement performance testing frameworks, analyze system bottlenecks, and work closely with development, DevOps, and architecture teams to optimize application and infrastructure performance.
You will also provide performance as a service infrastructure, developing self-service tools and frameworks that enable development teams to independently run, analyze, and fine-tune performance tests based on their specific needs.
This role requires deep hands-on expertise, strong analytical skills, and a proactive approach to performance optimization.
Your Role & Impact:
Architect, develop, and scale performance testing infrastructure for load, stress, endurance/longevity, and scalability testing.
Provide performance as a service, building self-service performance testing frameworks that allow development teams to execute and analyze tests autonomously.
Establish and enforce performance KPIs, ensuring optimal system behavior under various workloads.
Conduct in-depth performance analysis, identifying and resolving bottlenecks in APIs, databases, agent, caching, and distributed systems.
Lead the adoption of performance best practices, embedding them into the development and CI/CD pipelines.
Provide mentorship, best practices, and technical guidance to engineering teams, ensuring a performance-first mindset.
Enhance observability and monitoring capabilities, implementing APM tools like Prometheus/Grafana.
Analyze customers incidents, proactively identifying trends and areas for performance improvement.
Advocate for a shift-left approach, ensuring performance considerations are addressed early in the SDLC.
7+ years of experience in performance engineering, testing, and optimization, with at least 2 years in a technical leadership role.
Strong hands-on expertise with performance testing tools (JMeter, Locust, etc.).
Proven ability to mentor engineers, conduct code reviews, and instill best practices in automation and performance engineering.
Experience designing and implementing self-service performance testing platforms.
Proficiency in Python, Shell Scripts, groovy or another scripting language for performance automation.
Expertise with CI/CD pipelines and automation toolchains (e.g., Jenkins).
Deep understanding of cloud-native architectures containerization (Docker, Kubernetes, serverless), and microservices performance challenges.
Experience with databases (Postgres, serverless) and messaging systems (e.g. Kafka).
Expertise in profiling and monitoring tools (Grafana, Prometheus, Dynatrace, Pyroscope).
Proven ability to troubleshoot complex performance issues at the application, database, and infrastructure levels.
Passion for continuous improvement, automation, and engineering excellence.
