Engineering Manager, AI Platform - Managed AI

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.

This is an on-site role based in San Francisco, CA, or Sunnyvale, CA, requiring in-office presence

Team Leadership & Strategy: Lead, mentor, and grow a team of high-caliber software engineers on Crusoe’s 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.

Lead, mentor, and grow a team of high-caliber software engineers on Crusoe’s

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.

Technical Execution: 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.

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.

Collaboration and Influence: 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.

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.

Leadership Experience: 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.

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.

Technical Depth: 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.

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.

Product & Delivery Focus: 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.

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.

Preferred Qualifications: 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).

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).

Familiarity with open-source AI ecosystems (e.g., vLLM, Hugging Face, Triton).

Personal Attributes: Growth-minded leader who leads and empowers others. Excellent communicator and relationship builder. Passionate about building world-class AI infrastructure and teams

Growth-minded leader who leads and empowers others.

Excellent communicator and relationship builder.

Passionate about building world-class AI infrastructure and teams