The Performance Engineer will design, implement, and optimize performance solutions for systems and applications, leveraging AI for enhanced capabilities. Responsibilities include defining performance strategies, analyzing bottlenecks, and guiding teams in scalable architecture.
We are seeking a talented and experienced Performance Engineer to lead the design and implementation of high performance solutions across our systems, applications, and infrastructure. As a Performance Engineer, you will be
responsible for developing performance strategies, designing scalable architectures, and ensuring optimal performance across all platforms along with leveraging AI platforms. You will collaborate with cross-functional.
The candidate must have extensive experience in performance engineering, with a strong background in Performance Engineering for both backend systems and distributed environments along with hands on using AI to develop solutions and
tools. You will lead the creation of performance test strategies, identify bottlenecks, and provide architectural solutions to meet performance objectives. The role requires a deep understanding of performance testing,
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.
Technical Skills:
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.
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