About the Role: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
What You'll Be Working On:- 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.
- 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.
- 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.
What You'll Bring to the Team:- 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.
- 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.
- 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.
- 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).
- Personal Attributes:
- Growth-minded leader who leads and empowers others.
- Excellent communicator and relationship builder.
- Passionate about building world-class AI infrastructure and teams
Benefits:- Competitive compensation and equity packages
- Restricted Stock Units
- Paid time off, paid holidays & leave of absence programs
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
- Volunteer time off
- Global travel insurance & emergency assistance
- Daily meals allowance
- Additional perks & programs specific to location
Compensation RangeCompensation will be paid in the range of up to $215,000 - 260.000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.
