Senior Engineering Manager, AI Infrastructure
The Allen Institute for Artificial Intelligence
| Company | The Allen Institute for Artificial Intelligence |
| Category | Engineering |
| Location | Seattle |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 9 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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 de
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