Lead Software Engineer, 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

You are a visionary leader who occupies the space between high-level software orchestration and low-level system performance. You are motivated by the idea that world-class infrastructure should be a catalyst for public good, not a proprietary secret. You understand that in the world of frontier AI, the "software" and the "hardware" are a single, inseparable organism. You are as comfortable designing a distributed scheduling algorithm in Go as you are debugging a NCCL timeout or optimizing an Infini Band fabric.

You lead by example, blending the rigor of a Lead Software Engineer with the pragmatic, hands-on urgency of an HPC operator. Not only do you build systems, but you also ensure they thrive under the immense pressure of training world-class AI models.

While much of the AI industry has moved behind closed APIs, proprietary datasets, and "black box" infrastructure, Ai2 remains a lighthouse for Open Science. Founded by the late Paul Allen, we are a non-profit research institute dedicated to building AI for the common good.

We don't have a stock price to defend or a walled garden to protect. Instead, we have a mission: to provide the global research community with the transparent, high-performance foundations they need to achieve humanity-enriching breakthroughs.

• Radical Transparency: We don't just release model weights; we release the data, the training code, and the infrastructure insights. We believe the "how" is just as important as the "what."
• Mission over Margin: Our "bottom line" is scientific impact. This gives us the unique freedom to prioritize technical elegance, long-term stability, and open-source contributions over quarterly profit targets.
• The Best of Both Worlds: We operate at the pace and scale of a world-class tech startup but with the intellectual soul of a research lab.
• The Beaker Ecosystem: We build and operate systems like Beaker to coordinate the simultaneous training of frontier models (like OLMo) across massive GPU clusters. Our job is to ensure that the next great AI breakthrough isn't stalled by a resource bottleneck or a proprietary gatekeeper.

At Ai2, we believe that the most important AI breakthroughs should be transparent and accessible. Your challenge is to build the infrastructure that makes this possible. You will bridge the gap between our researchers, our orchestration platform (Beaker) and our GPU clusters.

You will be a technical lead responsible for ensuring that when a researcher submits a job, the software schedules it intelligently and the hardware executes it flawlessly. This involves:

• Designing for Scale: Architecting the next generation of our orchestration layer to ensure that the highest value workloads receive GPU time.
• Operational Excellence: Moving our HPC operations from manual intervention to high-level automation.
• Performance Engineering: Working directly with researchers to squeeze every bit of performance out of our GPU-accelerated computing environment.

• Strategic Leadership: Develop the roadmap for managing large-scale HPC systems, including the deployment of compute, networking, and storage in partnership with leadership.
• Full-Stack Ownership: Lead the design and delivery of critical systems that span the entire stack—from the Beaker job scheduler to the execution runtime.
• System Automation: Build innovative tooling and software-defined infrastructure to accelerate researcher velocity and automate cluster health management.
• Performance Optimization: Conduct root-cause analysis on complex distributed system failures and implement optimizations for distributed workloads.
• Mentorship & Culture: Foster a high-performance culture by reviewing code/design docs, mentoring team members, and driving process improvements…