Staff Engineer - Performance Engineering
MontyCloud19 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Define and drive organization-wide performance engineering strategy aligned with business KPIs, customer experience, and cost efficiency.
- Architect and build scalable self-service performance engineering platforms and AI-driven solutions for anomaly detection, predictive insights, adaptive load testing, and automated optimization.
- Design and execute large-scale performance testing for serverless, distributed, and event-driven systems.
- Establish performance benchmarks, SLAs, SLOs, KPIs, capacity-planning strategies, and continuous performance engineering practices.
- Integrate performance testing and validation into CI/CD pipelines.
- Identify and resolve bottlenecks involving latency, cold starts, concurrency, databases, networks, infrastructure, and resource utilization.
- Use observability, distributed tracing, and real-time monitoring to own performance in production environments.
- Lead scalability, capacity-planning, resilience, and cost-performance optimization initiatives for globally distributed systems.
- Collaborate with engineering, SRE, and architecture teams to influence system design and technical decisions.
- Mentor engineers and promote performance-first engineering practices across teams.
Requirements
- 8+ years of performance engineering experience in large-scale SaaS or cloud-native environments.
- 3+ years of experience in Senior, Lead, or Staff-level performance engineering roles.
- 4+ years of experience performance testing large-scale SaaS or distributed systems.
- 5+ years of hands-on experience with performance testing tools such as JMeter, Gatling, k6, or Locust.
- Experience designing and executing large-scale performance tests in production-like environments.
- Experience building performance engineering frameworks or platforms and integrating them into CI/CD pipelines.
- Experience optimizing distributed, event-driven, and serverless architectures, including latency, cold starts, concurrency, and scaling behavior.
- Experience identifying and resolving performance bottlenecks across application, database, network, and infrastructure layers, including database tuning at scale.
- Experience with observability and monitoring platforms, capacity planning, AI/ML-based optimization, and cloud cost-performance optimization.
- Experience influencing architecture and engineering decisions across teams and domains.
- Programming or scripting experience with Python, Java, or similar technologies.
- Experience with AWS and serverless services such as Lambda and API Gateway; Kubernetes, containerized architectures, chaos engineering, FinOps, multi-region systems, DynamoDB, Aurora Serverless, and AIOps are desirable.
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Strong analytical, communication, stakeholder-management, ownership, cross-functional leadership, and mentorship capabilities.