Principal Platform Engineer

Sakana AI is looking for a Principal Platform Engineer to lead the technical vision and architecture of our entire infrastructure platform. This is a senior individual contributor role — not management — where you will set the technical direction for how we build, deploy, and operate AI systems at the scale our ambitions demand. With $412M in funding and a research agenda that requires massive compute, the infrastructure decisions you make will have outsized impact on what Sakana AI can achieve.

You will be the person other engineers turn to when facing the hardest infrastructure problems: how to schedule heterogeneous GPU workloads across multiple clusters and cloud providers, how to build a model serving layer that handles both latency-sensitive inference and batch evolutionary search, how to design a data platform that supports the unique access patterns of nature-inspired training. You will produce architecture documents, lead design reviews, and make the calls on build-vs-buy decisions that shape our infrastructure for years.

Beyond technical architecture, you will mentor engineers across the organization, establish engineering standards and best practices, and help build a platform engineering culture that balances long-term technical vision with pragmatic execution. You will work directly with Sakana AI leadership to align infrastructure investments with research and business goals, translating compute requirements into capacity plans and budget forecasts.

The ideal candidate is a seasoned infrastructure leader who has built platforms serving millions of requests, managed large-scale GPU clusters, and can articulate a technical vision that inspires a team. You are recognized as a technical authority in infrastructure and can influence decisions across organizational boundaries without formal authority.

Requirements:

• 10+ years of infrastructure/platform engineering experience, including at least 3 years in a staff+ or principal role
• Proven track record of designing and building infrastructure systems at significant scale
• Experience leading technical architecture decisions across multiple teams and driving org-wide standards
• Deep expertise in distributed systems, networking, storage systems, and cloud-native architectures
• Hands-on experience with ML infrastructure: GPU cluster management, distributed training orchestration, model serving at scale
• Strong technical leadership skills with ability to mentor senior engineers and influence without authority
• Experience with capacity planning, cost optimization, and aligning infrastructure investments with business strategy