# Engineering Manager, AI Platform - Managed AI

**Company:** [Crusoe](https://hotfix.jobs/companies/crusoe)
**Location:** San Francisco, CA, Sunnyvale, CA
**Role:** Engineering Management
**Salary:** $215k – $260k/yr
**Experience:** 8+ years
**Skills:** Python, Go, Rust, Kubernetes, gRPC, Observability, Distributed Systems, concurrent systems, cloud-native architecture, container orchestration, AI Infrastructure, llm systems, vLLM, hugging face, triton
**Posted:** 2026-08-13

> Leads and scales an engineering team building a fault-tolerant managed AI platform for LLM workloads, including task queues, model management, scheduling, and agentic execution infrastructure. Requires 5+ years leading engineering teams plus depth in distributed systems, cloud-native platforms, and AI infrastructure.

## Job Description

## Responsibilities

### Team Leadership & Strategy
- Lead, mentor, and grow a team of high-caliber software engineers.
- Partner with leadership to define and execute the AI roadmap, set clear goals, and drive accountability.
- Cultivate a high-performance, collaborative engineering culture grounded in technical excellence.

### Technical Execution
- Oversee the architecture and development of core AI services, including fault-tolerant task queues, model management systems, and cost-aware scheduling.
- Ensure delivery of scalable systems capable of handling millions of API requests per second.
- Deliver an AI platform capable of supporting workloads ranging from model 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.

## Requirements

### Leadership Experience
- 5+ years managing or leading high-performing engineering teams.
- Ability to lead teams through ambiguity and align stakeholders 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 service-oriented architectures.
- Familiarity with CPU and GPU performance, inference frameworks, or LLM systems.

### Product and Delivery
- 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, Go, or Rust.
- Experience with Kubernetes, gRPC, and observability stacks.
- Familiarity with open-source AI ecosystems such as vLLM, Hugging Face, and Triton.

## Benefits and Compensation

- Competitive compensation and equity packages.
- Restricted Stock Units.
- Paid time off, paid holidays, and leave of absence programs.
- Comprehensive health, dental, and vision insurance.
- Employer contributions to an HSA.
- Paid parental leave.
- Paid life insurance and short- and long-term disability coverage.
- Professional development and tuition reimbursement.
- Mental health and wellness support.
- Commuter benefits for parking and transit.
- Cell phone stipend.
- 401(k) retirement plan with company match up to 4% of salary.
- Volunteer time off.
- Global travel insurance and emergency assistance.
- Daily meals allowance.
- Additional location-specific perks and programs.
- Compensation range: $215,000 - $260,000 plus bonus. Restricted Stock Units are included in all offers.

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