Senior/Principal Performance Engineer

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CIQ OVERVIEW CIQ builds the enterprise infrastructure that powers the world's most demanding workloads. From the operating system layer through AI infrastructure, high-performance computing, and cloud-native orchestration, CIQ delivers the speed, security, scalability, and sovereignty that major enterprises, government agencies, and research institutions depend on. CIQ is the founding support and services partner of Rocky Linux and the developer of the RLC Pro family of Enterprise Linux distributions, Fuzzball workload orchestration, Warewulf Pro cluster provisioning, and Ascender Pro automation. Our customers include some of the largest and most technically sophisticated organizations in the world, working across HPC, AI/ML, defense, and regulated industries. We are a company of builders, operators, and open source practitioners. If you want to do work that matters, at a company that is genuinely changing how enterprise infrastructure gets built and run, we want to talk. CIQ is seeking a highly experienced Senior or Principal Performance Engineer to own and drive system-level and application-level performance across our product portfolio. This is an AI-first role, both in methodology and focus area, and the right candidate will bring deep expertise in operating system internals, kernel and userspace performance, and the performance demands of modern AI workloads, HPC environments, general-purpose computing, and production service workloads. In this role, you will be the standard-bearer for performance at CIQ. Our performance-focused solutions must always be the fastest in the industry, and you will be responsible for ensuring that remains true. You will be intimately involved with Fuzzball, CIQ's cloud-native computing platform, learning its architecture end-to-end and integrating workloads - both user-facing and CI/testing pipelines - directly through it. Position Summary This role is leveled as Senior or Principal based on qualifications and demonstrated capabilities. Benchmarking & Profiling Design, develop, and maintain comprehensive benchmarking frameworks spanning OS, kernel, and application layers. Profile workloads across CPU, memory, I/O, network, and accelerator (GPU/NPU) subsystems to identify bottlenecks and optimization opportunities. Establish and own performance baselines across CIQ's product and solutions portfolio. Leverage AI-assisted tooling and agentic workflows to accelerate profiling, analysis, and root cause identification. Regression Detection & Resolution Build and maintain automated performance regression-detection pipelines integrated into CI/CD workflows using Fuzzball. Identify, triage, and resolve regressions across user space, kernel space, and application layers with urgency and rigor. Collaborate across engineering teams to root-cause regressions introduced by upstream kernel changes, compiler updates, or library modifications. Proactive Performance Engineering Drive proactive performance improvements - not just reactive fixes - to keep CIQ solutions ahead of the competition across every layer of the stack. Own core operating system performance: kernel subsystem tuning (scheduler, memory management, I/O, networking), system call overhead reduction, and user space library and runtime optimizations. Identify and implement kernel-level enhancements, including patches, configuration changes, and upstream contributions that yield measurable performance gains for CIQ's customer workloads. Optimize for AI inference and training workloads, including LLM serving, model parallelism, and accelerator utilization. Tune performance for HPC workloads, including modeling, simulation, and tightly coupled parallel applications (MPI, OpenMP, etc.). Optimize general computing and service workloads - web services, databases, messaging systems, and other production software that runs on CIQ's OS platform. Work at all levels of the stack: compiler flags, kernel parameters, scheduler tuning, NUMA topology, memory allocation, and application-level algorithmic improvements. AI-First Approach Champion an AI-first engineering philosophy - use AI tools, agents, and automation to accelerate your own productivity and the quality of performance insights. Identify and prioritize optimization opportunities that directly impact AI training throughput and inference latency/cost. Stay current on state-of-the-art techniques in ML system performance, including quantization, batching strategies, kernel fusion, and hardware-software co-design. Fuzzball Integration Develop deep expertise in CIQ's Fuzzball platform - its architecture, scheduling, and workload execution model. Integrate performance benchmarks, regression tests, and user-facing workloads into Fuzzball-based pipelines. Contribute to the performance characterization of Fuzzball itself, ensuring the platform adds minimal overhead and scales efficiently. Cross-Functional Collaboration Develop broad familiarity with the fu

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