Staff Software Engineer, Managed AI

Crusoe is building the World’s Favorite AI-first Cloud infrastructure company. We’re pioneering vertically integrated,  purpose-built AI infrastructure solutions trusted by Fortune 500 companies to power their most advanced AI applications. Crusoe is redefining AI cloud infrastructure, with a mission to align the future of computing with the future of the climate. Our AI platform is recognized as the "gold standard" for reliability and performance. Our data centers are optimized for AI workloads and are powered by clean, renewable energy.

Be part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that’s setting the pace for responsible, transformative cloud infrastructure.

About the Role

As a Senior/Staff Software Engineer on the Managed AI team at Crusoe, you'll have a pivotal role in shaping the architecture and scalability of our next-generation AI inference platform. You will lead the design and implementation of core systems for our AI services, including resilient fault-tolerant queues, model catalogs, and scheduling mechanisms optimized for cost and performance. This role gives you the opportunity to build and scale infrastructure capable of handling millions of API requests per second across thousands of customers.

From day one, you'll own critical subsystems for managed AI inference, helping to serve large language models (LLMs) to a global audience. As part of a dynamic, fast-growing team, you’ll collaborate cross-functionally, influence the long-term vision of the platform, and contribute to cutting-edge AI technologies. This is a unique opportunity to build a high-performance AI product that will be central to Crusoe's business growth.

A Day In the Life

As a Senior/Staff Software Engineer in the Managed AI team, you’ll play a crucial role in building the infrastructure to serve artificial neural networks and in the near term, large language models (LLMs) at scale. You’ll own the design and implementation of key subsystems for resiliency and quality of service. You will build model catalogs, billing systems, dynamic pricing models, and have the opportunity of going deep into the model deployment stack for cost-optimized scheduling. Each day, you’ll collaborate with a small but growing team of engineers to build scalable cloud-based solutions that can handle millions of requests per second.

You’ll work closely with cross-functional teams, including product management and business strategy, to develop a customer-facing API that serves real-world AI models. Every day will present an opportunity to influence the long-term vision and architectural decisions, from the first lines of code to full-scale implementation. You’ll also be prototyping rapidly, optimizing performance on GPUs, and ensuring high availability as part of the MVP development. Whether it’s contributing to open-source AI frameworks or diving into low-level performance optimizations, your contributions will directly impact both the company’s growth and the product’s success.

You Will Thrive In This Role If You Have:

• You have a strong background in distributed systems design and implementation, with proven experience in early-stage projects and tight deadlines.

• You are passionate about building scalable AI infrastructure and have experience with cloud-based services that can handle millions of requests.

• You enjoy problem-solving around performance optimizations, particularly when it comes to AI inference on GPU-based systems.

• You have a proactive and collaborative approach, with the ability to work autonomously while engaging with a rapidly growing team.

• You have strong communication skills, both written and verbal, and can translate complex technical challenges into understandable terms for cross-functional teams.

• You’re excited about working in a fast-paced environment, contributing to a new product category, and having a tangible influence on the long-term vision of the AI platform.

• You are passionate about open-source contributions and AI inference frameworks like VLLM, with a desire to push the boundaries of performance and scalability.

• You are keen on customer-facing product development, with a desire to build user-friendly APIs that integrate real-world feedback for continuous improvement.

Preferred Qualifications

• Must-Have:

  • Advanced degree in Computer Science, Engineering, or a related field.

  • Demonstrable experience in distributed systems design and implementation.

  • Proven track record of delivering early-stage projects under tight deadlines.

  • Expertise in using cloud-based