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VESSL AI

GPU cloud platform for AI workloads

Technical Program Manager

Program ManagementConfirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedHybrid

About the Job

Requirements

  • A bachelor's degree or higher in a related field such as Computer Science or Industrial Engineering.
  • At least 6 years of experience as a Technical Program Manager, Product Manager, or Project Manager.
  • A foundational understanding of the technical structure of cloud, data center, or GPU infrastructure, including compute, networking, and storage.
  • Experience designing customer-facing service-level agreements based on service-level indicator and service-level objective data and securing agreement across multiple organizations.
  • Experience working directly with engineering roles such as Site Reliability Engineers, Software Engineers, and Security Engineers to coordinate technical priorities.
  • Experience gathering data from stakeholders with different backgrounds, including engineering, sales, and executives, to drive decisions.
  • Experience structuring and managing risks and dependencies in complex programs.
  • Ability to analyze data and build dashboards using SQL or similar tools.
  • Business-level English communication skills.

Responsibilities

  • Integrate the Supply organization's plans for securing new capacity with Demand forecasts, manage the medium- and long-term capacity plan, and continuously update it.
  • Coordinate and track the schedule for onboarding new clusters secured by the Supply organization, from validation and network and scheduler integration through readiness for sale on the platform, in coordination with SRE and Infrastructure.
  • Design customer-facing service-level agreements based on SRE service-level indicator and service-level objective data, and lead discussions with SRE, Product, and Sales leadership to reach final agreement.
  • Establish capacity allocation policies across sales types such as on-demand, reserved instances, and spot, and track and report actual allocation status.
  • Work with Site Reliability Engineering, Software Engineering, and Security Engineering to set priorities and coordinate execution of infrastructure projects, including site reliability and compliance projects.
  • Design and operate recurring program forums such as Capacity Review; plan and build supply-demand visibility tools with the team’s Software Engineers; and establish dashboards and reporting for executives and related organizations.
  • Identify risks from supply delays, onboarding delays, demand surges, and infrastructure outages; escalate them to relevant organizations and develop mitigation plans together.

Desired Qualifications

  • Experience managing a capacity-planning program at an organization operating large-scale GPU or high-performance computing clusters, or at a cloud service provider.
  • Understanding of Site Reliability Engineering practices such as service-level objectives, service-level agreements, on-call, and incident management or postmortems.
  • Experience participating in projects related to security or compliance frameworks such as SOC 2.
  • Understanding of procurement and contracting processes with cloud service providers or data centers.
  • Understanding of scheduling and orchestration environments such as Kubernetes and Slurm.
  • Experience designing processes from the ground up in a startup or hypergrowth environment.
  • Comfort solving problems across diverse organizations without being restricted to a predefined scope.
  • Comfort independently structuring and solving ambiguous problems without predetermined answers.

About the Company

VESSL AI

GPU cloud platform for AI workloads

What VESSL AI does: It runs VESSL Cloud, a GPU cloud platform built for AI workloads. It gives teams on-demand access to high-end GPUs (A100, H100, B200, B300, GB200) to run activities like LLM fine-tuning, large-scale model training, and AI inference. How it works: Users launch GPU instances in VESSL Cloud from VESSL’s own data center infrastructure, paying per minute for usage, and using the platform to accelerate AI development without managing physical hardware. How it stands out: It operates its own data center and offers per-minute billing, delivering up to 80% cost savings versus AWS and GCP, focusing specifically on AI workloads rather than general-purpose cloud services. What the goal is: To help AI teams move quickly from idea to production by removing infrastructure overhead and providing scalable, affordable GPU resources for AI work.

Company size
51-200
Company stage
Series A
Total funding
$16.6M
Headquarters
San Francisco, CA
Founded
2020

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