Senior Staff Software Engineer, Crusoe Energy Systems

• 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
• Experience in Generative AI (Large Language Models, Multimodal)
• Familiarity with AI infrastructure, including training, inference, and ETL pipelines
• 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
• 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

Desirable

• 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
• 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
• 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
• 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