1 day ago
Kraków, PolandStaff+
Responsibilities
- Lead performance investigations from hypothesis and instrumentation through customer-visible production improvements.
- Architect and re-architect distributed, petabyte-scale subsystems involving memory hierarchy, concurrency, I/O, and tail latency.
- Own performance methodology, including profiling, flame-graph analysis, lock-contention analysis, benchmarking, and CI regression gating.
- Introduce telemetry, eBPF, and continuous profiling for production performance observability.
- Quantify trade-offs, risks, and expected outcomes for directors, managers, engineers, and customers.
- Build reusable AI-agent workflows and tooling to accelerate performance analysis and delivery.
- Lead, mentor, and grow engineers while influencing senior and staff peers through technical leadership.
Requirements
- Expert-level production C++ experience, including memory management, allocators, move semantics, cache-friendly data structures, and language cost models.
- Deep performance-engineering experience across CPU and memory profiling, flame graphs, lock contention, latency optimization, benchmarking, performance modeling, and architecture design.
- Production experience with several performance areas including perf, eBPF, VTune, off-CPU profiling, continuous profiling, atomics, memory ordering, lock-free techniques, and distributed-system latency analysis.
- Experience with Docker and Kubernetes in containerized performance environments.
- Strong Python experience for tooling, benchmark harnesses, telemetry pipelines, and performance-data analysis.
- Strong knowledge of Linux performance internals, including the scheduler, memory subsystem, page cache, filesystems, block I/O, and network stack.
- Experience with Git and CI automation for builds, tests, benchmarks, and releases, such as GitLab CI.
- Track record of informing leadership decisions through quantitative trade-off analysis and communicating clearly across technical and business audiences.
- Daily use of AI coding agents and experience building agentic workflows while verifying output against profiles, benchmarks, and telemetry.
- Bachelor's degree plus 12 years, master's degree plus 8 years, or PhD plus 5 years of related experience.
- Preferred: petabyte-scale ingest, storage, retrieval, search, object-storage, caching, eviction, or I/O workload experience.
- Preferred: Splunk internals or comparable search, analytics, large-scale data-platform, storage, query-engine, or distributed-search experience.
- Preferred: hardware-level optimization involving SIMD, NUMA, cache/TLB behavior, PGO/LTO, or compiler optimization.
- Preferred: Go, Rust, or another systems language alongside C++.
- Preferred: AWS, Azure, or GCP storage, networking, and instance-performance experience.
- Preferred: Terraform, Puppet, or Ansible experience for reproducible performance-test environments.
Benefits
- Flexible hybrid work model balancing work from home and in-office collaboration.
- Career growth through technical ownership, leadership opportunities, coaching, mentorship, and a collaborative team environment.
- Opportunities to work on petabyte-scale performance problems with measurable customer impact and exposure to new technologies and open-source projects.
Tech Stack
Categories
About Cisco
Cisco designs and sells networking, security, and collaboration platforms for enterprises, service providers, and governments, spanning routers and switches, Wi‑Fi, firewalls, zero‑trust, observability, and cloud-managed IT (Meraki) plus Webex. Its business model mixes hardware, software subscriptions, and support/consulting services. Founded in 1984 and headquartered in San Jose, California, Cisco is a public company traded on Nasdaq and serves customers across data centers, campuses, and service provider networks.