WHAT YOU WILL BE DOING
- Architect and Design performance-optimized solutions for complex systems, ensuring scalability, reliability, and cost-effectiveness.
- Define and implement performance strategies across the organization, including testing, tuning, and monitoring plans.
- Analyze system performance from end to end, identifying performance bottlenecks and providing architectural recommendations for optimization.
- Lead performance engineering efforts, ensuring robust and scalable designs through every phase of the development lifecycle.
- Leverage AI platforms to enhance and solution for performance activites
- Collaborate with development, operations, and business teams to ensure performance standards are met throughout the infrastructure.
- Ensure the effective use of performance testing tools and monitoring solutions, including designing load models,test cases, and reporting frameworks.
- Perform architectural reviews of systems with a focus on identifying and eliminating performance bottlenecks.
- Guide the team in capacity planning and scalability strategies for current and future growth.
- Oversee the execution of benchmarking, load testing, stress testing, and endurance testing to validate performance targets.
- Performance Testing Tools: Expertise in JMeter and performance testing frameworks (e.g., Gatling,LoadRunner).
- Programming/Scripting: Proficient in Java, JavaScript, and shell/bash for performance automation.
- Monitoring & Profiling: Experience with Heap Dumps, GC Logs, and tools like Datadog, AppDynamics,Dynatrace, Grafana.
- Cloud: Familiar with AWS, GCP, or Azure for cloud performance optimizations.
- Containers & Orchestration: Knowledge of Docker and Kubernetes for containerized environments.
- CI/CD Automation: Experience with GitLab, GitHub, Jenkins for integrating performance tests in CI/CD pipelines.
- AI : Any AI tools and relevant prompt engineering to leverage it for solutions and tools.
WHAT YOU BRING
- Bachelor’s or Master’s Degree in Computer Science, Engineering, or related fields.
- 12+ years of experience in performance engineering, with at least 4 to 6 years in a Performance Engineer or similar role.
- Architectural Expertise: Deep understanding of distributed systems, microservices architecture, and cloud-native environments (AWS, GCP, Azure).
- Performance Engineering Tools: Expertise in performance tools such as JMeter, LoadRunner, Gatling, Dynatrace, AppDynamics, Datadog, Grafana, Prometheus, and custom-built tools for real-time monitoring and testing.
- Programming and Scripting: Proficiency in Java, JavaScript, Python, or other programming languages to implement performance optimizations and automate testing and monitoring workflows.
- AI Tools : Experience in AI to develop solutions and tools to complement the performance activities.
- Cloud and Containerization: Experience with cloud platforms (AWS, GCP, Azure) and containerization/orchestration technologies like Docker and Kubernetes. Expertise in cloud-native architectures and edge service optimizations.
- Deep Analytical Skills: Ability to analyze system performance metrics (e.g., CPU usage, memory, network I/O,disk I/O, garbage collection) and provide architectural solutions to improve performance.
- Capacity Planning: Experience with capacity management and planning to ensure that systems can scale under increasing user demand without degrading performance.
- Collaboration and Leadership: Strong collaboration skills to work with developers, product managers, DevOps, and business teams. Ability to lead performance discussions and architectural improvements.