Related skills
kubernetes observability tracing benchmarking profiling📋 Description
- Lead deep performance investigations across distributed services and multi-region systems.
- Analyze latency, throughput, saturation, and concurrency across data and control planes.
- Collaborate with platform/infra teams to optimize runtime, networking, containers, and resources.
- Define performance standards, benchmarking strategies, and system-level expectations.
- Influence architectural decisions to improve scalability, resiliency, and operational efficiency.
- Design AI-assisted performance workflows for scalable validation across systems.
🎯 Requirements
- 8+ years of software engineering in distributed systems and large-scale infrastructure.
- Strong understanding of networking, concurrency, caching, replication, and scaling.
- Proven track record of identifying and resolving bottlenecks in production systems.
- Experience designing and executing performance tests for distributed systems.
- Expertise in observability, profiling, tracing, benchmarking, and analysis tools.
- Systems-level thinking balancing reliability, scalability, and cost.
- Ability to influence technical direction across teams without direct authority.
- Excellent communication and collaboration in cross-functional environments.
🎁 Benefits
- Experience optimizing cloud-native platforms on Kubernetes or similar container orchestration.
- Familiarity with performance engineering in fintech or highly regulated industries.
- Experience building AI-assisted engineering workflows or agent-driven validation systems.
- Background working with multi-region architectures and globally distributed services.
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