Senior Manager, Infrastructure Platform Engineering

Crusoe

↗

Software Development 👥 501 employees 📍 Denver, Colorado, US Est. 2018

Crusoe is the industry’s first vertically integrated, purpose-built AI cloud platform. The company is redefining AI cloud infrastructure and its platform is recognized as the "gold standard" among bu…

Job Overview

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

About the Role

We are seeking a Senior Manager, Infrastructure Platform Engineering to lead a team building core systems that turn large-scale compute infrastructure into reliable, secure, and efficiently allocatable capacity. The team owns foundational services spanning resource pooling and allocation, capacity and utilization intelligence, fleet and system lifecycle management, and platform security and trust.

This is a hands-on management role for a leader who has come up through infrastructure and systems software engineering, understands the realities of operating compute at scale across cloud and on-premise environments, and is energized by building the control and platform systems that other engineering teams depend on. You'll lead a growing team of infrastructure software engineers, set technical direction across the platform, and partner closely with adjacent infrastructure, production engineering, and security teams to keep the substrate reliable, well-utilized, and easy to build on.

While this is an infrastructure-focused role rather than a traditional product role, the systems this team builds are essential to the experience our customers have on the platform. Reliable capacity, healthy systems, and a trustworthy substrate are what make a seamless, dependable customer experience possible — so the team's work directly underpins the business, even as its immediate users are the internal engineering teams building and operating workloads on top of it.

What You'll Be Working On

• Leading the team responsible for the platform services that abstract underlying infrastructure into reliable, allocatable capacity, and for the systems that track and reconcile state across a large fleet


• Setting the technical roadmap across capacity and utilization intelligence, resource lifecycle and state management, and platform security and trust frameworks


• Driving the design of secure, well-instrumented platform systems — from Kubernetes-based orchestration and automation to lower-level system and hardware integration


• Hiring, mentoring, and growing a team of infrastructure software engineers; building a high-performing organization from a strong foundation


• Partnering with infrastructure, production engineering, and security teams to align platform capabilities with operational reliability, capacity, and trust requirements


• Improving platform efficiency and availability — characterizing bottlenecks, reducing stranded resources, and shortening operational and recovery cycles


• Establishing engineering standards for infrastructure software development: code quality, testing, deployment safety, and on-call practices for systems that span the platform


• Translating a vertically integrated infrastructure stack into reliable platform primitives that engineering teams can build on


• Staying technically hands-on — reviewing designs, contributing to architecture decisions, and being credible to the engineers you lead

What You'll Bring to the Team

• 10+ years of experience in infrastructure or systems software development, with at least 3+ years in an engineering leadership role


• Deep expertise in large-scale infrastructure platforms — building services that pool, allocate, and reconcile compute resources at scale


• Strong background with Kubernetes and cloud platforms (GCP, AWS, or Azure) — orchestration, automation, and operating distributed systems in production


• Experience with distributed state management and control systems — modeling resource and system lifecycle, reconciling desired vs. actual state, and handling failure gracefully across a large fleet


• Experience with efficiency, capacity, or performance engineering — characterizing system behavior, identifying bottlenecks, and driving measurable improvements in utilization or availability


• A player-coach approach to management: hands-on enough to make technical calls, structured enough to grow a team and ship through them


• Track record of hiring strong infrastructure engineers and helping them grow into more senior roles


• Comfortable operating in a fast-moving environment where the path isn't fully paved — willing to drive ambiguity to clarity

Bonus Points

• Experience operating Kubernetes on bare-metal infrastructure as well as on managed cloud services (GKE, EKS, AKS)


• Familiarity with the operational challenges of GPU clusters, AI training, and inference workloads


• Working knowledge of platform security and trust concepts — secure boot, measured boot, TPMs, and hardware attestation


• Experience with capacity forecasting, demand modeling, or allocation optimization at scale


• Hands-on background with telemetry and observability systems for large-scale distributed platforms