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 This Role:

As a 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.

What You’ll Be Working On:

• Design and Development:

  • Lead the design and implementation of core AI services, including:

    • Resilient fault-tolerant queues for efficient task distribution.

    • Model catalogs for managing and versioning AI models.

    • Scheduling mechanisms optimized for cost and performance.

    • High-performance APIs for serving AI models to customers.

• Scalability and Performance:

  • Build and scale infrastructure to handle millions of API requests per second.

  • Optimize AI inference performance on GPU-based systems.

  • Implement robust monitoring and alerting to ensure system health and availability.

• Collaboration and Innovation:

  • Collaborate closely with product management, business strategy, and other engineering teams.

  • Influence the long-term vision and architectural decisions of the AI platform.

  • Contribute to open-source AI frameworks and participate in the AI community.

  • Prototype and iterate on new features and technologies.

What You’ll Bring to the Team:

• Strong Engineering Fundamentals:

  • 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 services, such as, elastic compute, object storage, virtual private networks, managed database, etc.

• AI/ML Expertise:

  • Experience in Generative AI (Large Language Models, Multimodal).

  • Familiarity with AI infrastructure, including training, inference, and ETL pipelines.

• Software Engineering Skills:

  • Experience with container runtimes (e.g., Kubernetes) and microservices architectures.

  • Experience using REST APIs and common communication protocols, such as gRPC.

  • Demonstrated experience in the software development cycle and familiarity with CI/CD tools.

• Preferred Qualifications:

  • Proficiency in Golang or Python for large-scale, production-level services.

  • Contributions to open-source AI projects such as VLLM or similar frameworks.

  • Performance optimizations on GPU systems and inference frameworks.

• Personal Attributes:

  • Proactive and collaborative approach with the ability to work autonomously.

  • Strong communication and interpersonal skills.

  • Passion for building cutting-edge AI products and solving challenging technical problems.

Benefits:

• Hybrid work schedule