Global Capacity Manager

present of AI; San Francisco (CA); Remote; USD 190,000 - 260,000; Full time

Job summary

Baseten is seeking a Senior Operations Engineer to run the supply and health of a large GPU fleet, primarily in a remote-friendly environment with on-site SF presence. You will ensure capacity, reliability, and smooth workload movement across clouds, while building software to scale operations.

The ideal candidate has deep hands-on Kubernetes experience, writes production-grade Go or Python, and can model the cost of reliability against spend.

Qualifications

• Hands-on Kubernetes experience in production environments.
• Ability to write reliable code in Go or Python.
• Experience modeling cost and reliability trade-offs.

Responsibilities

• Manage GPU fleet health, capacity, and provisioning.
• Move customer workloads between clouds and optimize throughput.
• Lead incident response and post-incident reviews with SRE teams.
• Build software to improve scalability and reliability of the platform.
• Collaborate with infrastructure to guide capacity planning and budgeting.

Skills

Kubernetes

Go

Python

Cost modeling

Incident response

SRE collaboration

Tools

Kubernetes

Cloud platforms (AWS/GCP)

Job description

Operations · San Francisco · Remote · FullTime · Senior level

This role runs the supply and health of a large GPU fleet. That covers buying capacity, keeping clusters healthy, moving customer workloads between clouds, and building the software that makes it scale. A strong candidate has years of hands-on Kubernetes work, writes production Go or Python, and can model the cost of reliability against spend. Calm handling of outages and steady teamwork with SRE and infrastructure colleagues matter as much as the technical depth.

How it fits the AI era

AI demand drives everything here, since customers' models need scarce, fast-changing chips, and the job is making sure those chips are available and used well. Automation can take over node triage, repair and workload moves, so the value shifts toward designing those systems and deciding what to build next. Judgment on supplier deals, cost trade-offs and incident calls stays with people.

How it builds AI experience

The work puts a person close to how real AI inference runs at scale, including new hardware like Blackwell GPUs and how different models use capacity. Someone could build that background by running GPU workloads on Kubernetes, trying open-source model serving tools, and learning how GPU cost per request is worked out. Working with a platform that serves many AI companies gives a wide view of how the industry uses compute.

Worth showing

• Kubernetes operators in Go
• GPU or cloud capacity planning
• Cost and ROI modeling
• Incident response leadership

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Baseten

High-performance cloud inference platform for deploying, serving, and scaling open-source and custom artificial intelligence models.