This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
As an Engineering Manager on the Managed AI team at Crusoe, you will play a critical role in leading and scaling a team of engineers building our next-generation platform for the full lifecycle of Large Language Models (LLMs). You will be responsible for guiding the team through the design and implementation of highly scalable, fault-tolerant infrastructure. You will lead a team of high-caliber engineers, combining technical expertise with strong people leadership. This role is central to a fast-growing, strategically important organization, where you will shape the engineering roadmap and drive the execution of key projects. Success requires close partnership with product, business, and platform stakeholders to deliver a performant and reliable platform that powers AI for customers globally.
Job Responsibility:
Lead, mentor, and grow a team of high-caliber software engineers
Partner with leadership to define and execute the AI roadmap, setting clear goals and driving accountability
Cultivate a high-performance, collaborative engineering culture grounded in technical excellence
Oversee the architecture and development of core AI services: fault-tolerant task queues, model management systems, cost-aware scheduling, etc.
Ensure delivery of scalable systems capable of handling millions of API requests per second
Deliver an AI platform that can handle a large variety of load from training, to agentic execution infrastructure
Work cross-functionally with Product, Infrastructure, and GTM stakeholders
Represent Engineering in strategic discussions to influence AI platform growth and customer adoption
Promote knowledge sharing, technical mentorship, and the evolution of engineering processes
Requirements:
5+ years managing/leading high-performing engineering teams
Ability to lead teams through ambiguity and align on complex technical goals
Proven success hiring, developing, and retaining talent
Hands-on experience with distributed and concurrent systems or AI infrastructure
Deep knowledge of cloud-native environments, container orchestration, and SOAs
Some familiarity with CPU & GPU performance, inference frameworks, or LLM systems is a strong plus
Comfortable owning deliverables from design through production
Strong collaboration skills, prioritizing clarity, context, and customer impact
Experience in fast-paced startup or growth-stage environments
Background in Computer Science, Engineering, or a related technical field
Proficiency in Python/GoLang/Rust
Experience with Kubernetes, gRPC, and observability stacks
Familiarity with open-source AI ecosystems (e.g., vLLM, Hugging Face, Triton)
Growth-minded leader who leads and empowers others
Excellent communicator and relationship builder
Passionate about building world-class AI infrastructure and teams