Senior Engineering Manager, AI Infrastructure

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter. Our base salary range is $146,880 - $220,320, and in addition we have generous bonus plans to provide a competitive compensation package.  Who You Are: We are seeking a Senior Manager, AI Infrastructure to run the day-to-day operation of the systems that power our research. Reporting to the VP of Engineering, you will own the execution and reliability of our high-performance computing (HPC) environment which includes on-prem GPU clusters and the software orchestration layer that schedules workloads across a hybrid cloud environment. This is a hands-on operational leadership role: your mandate is to keep the platform fast, reliable, and well-utilized, and to deliver against the roadmap set with your PM counterpart. Our ideal candidate is a: Systems Expert: You have a deep, hands-on understanding of the Linux kernel, container runtimes, and distributed systems. You understand the performance implications of InfiniBand topologies and NCCL optimizations. Execution-Focused Leader: You plan and deliver against near-term operational goals, keep reliability and researcher velocity high, and turn priorities set with leadership into shipped, dependable systems. Pragmatic Operator: You are comfortable making trade-offs between technical elegance and operational necessity. You triage and mitigate immediate risks, and know when to handle something yourself versus escalate. Who We Are:  Ai2 is a non-profit research institute at the forefront of open-source AI development. Unlike industry peers, our goal is to share our findings, data, code, and models with the global scientific community.  Why Ai2: Open Science: Your work directly enables the release of open models like OLMo, providing the broader research community with tools they can't get elsewhere. Mission-Driven: We prioritize scientific impact over profit margins. This allows us to focus on building the "right" infrastructure for long-term research goals. Complexity at Scale: You will manage some of the most dense and high-performance compute environments currently in operation. Your Next Challenge: Cluster Operations: Manage the availability, performance, and health of our dense on-prem GPU clusters. Coordinate with hardware vendors and internal teams to keep physical infrastructure meeting the demands of frontier model training. Orchestration & Scheduling: Operate and improve Beaker, our internal orchestration platform by optimizing resource allocation and driving high utilization across on-prem assets and elastic cloud resources (AWS/GCP). Storage Operations: Execute and continuously improve our storage environment, balancing high-throughput performance for active training against cost-effective durability for petascale research data. Contribute to the longer-term storage roadmap. Resource Management: Manage GPU compute allocation against budget. Track utilization, surface the data, and recommend when to burst to the cloud versus investing in on-prem capacity, escalating larger trade-offs as needed. User Support & Velocity: Serve as the technical bridge to our research teams. Ensure infrastructure is an accelerator, not a bottleneck, for a diverse set of research objectives. Team Leadership: Manage and grow a team of systems engineers, SREs, and software developers. Set the bar for operational rigor, engineering quality, and a collaborative culture, and keep the team unblocked and delivering. What You’ll Need: Experience: 12+ years in infrastructure, systems engineering, or HPC (or an advanced degree with 8+ years), including 2+ years supervising a small engineering team (5+). Bachelor's degree in a related field : a relevant advanced degree may substitute for equivalent years of technical work experience. GPU/HPC Stack: Direct experience operating large-scale NVIDIA GPU clusters and high-performance networking (InfiniBand/RoCE). Orchestration: Strong background in Kubernetes, Slurm, or similar orchestration frameworks, particularly in hybrid-cloud configurations. Storage: Hands-on experience with distributed filesystems (e.g., WEKA, Ceph, Lustre) and cloud storage integration at scale. Software Development: Proficient in designing and managing SDLC processes including sprint planning and technical design reviews. Proficient in Go or Python. Physical Demands and Work Environment: The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions. Must be able to remain in a stationary position for long periods of time.  The ability to communicate information and ideas so others will unde