General Manager - AI Compute & Infrastructure

Gomining; United States; Hybrid; USD 180,000 - 320,000; Full time

Benefits offered by this job

Remote or hybrid work

Flexible hours across international 팀s

Paid vacation and company holidays

Global team retreats

Professional growth support

Job summary

Gomining seeks an entrepreneurial leader to build and scale an AI compute business within a global company. You will own GPU procurement, AI infra development, and compute sales, partnering with NVIDIA, OEMs, and cloud providers.

You will work with leadership to shape strategy, run financially disciplined programs, and build a high-performance team to deliver revenue growth and robust unit economics in a fast-moving market.

Qualifications

• 2+ years in AI infrastructure, GPU cloud, data centers.
• Proven track record of launching or scaling infra-driven businesses.
• Strong understanding of GPU computing and the AI ecosystem.
• Experience in two or more areas listed in qualifications.

Responsibilities

• Lead GPU procurement strategies and strategic partnerships.
• Oversee AI infrastructure development and deployment.
• Drive AI compute sales and commercialization.
• Own business strategy, unit economics, and roadmap execution.
• Build and lead a team to scale the business.

Skills

Entrepreneurial mindset

Strategic partnerships

GPU computing

Infra development

Sales & commercialization

Negotiation

Financial modeling

Team leadership

Independent decision-making

Fluent English

Job description

This is a unique opportunity to build an AI infrastructure business within an established international company.

We are looking for an entrepreneurial leader who understands the GPU compute ecosystem and can turn infrastructure investments into a scalable, revenue-generating business.

You will take ownership of three core areas:

1. GPU Procurement & Strategic Partnerships
2. AI Infrastructure Development & Deployment
3. AI Compute Sales & Commercialization

You will work closely with company leadership to develop the business strategy, establish strategic partnerships, identify investment opportunities, and execute the roadmap.

This is a hands-on leadership role requiring a combination of commercial expertise, infrastructure knowledge, and strong execution capabilities.

We are not looking for someone who simply manages existing operations. We need someone who can build the business.

Responsibilities

1. GPU Procurement & Strategic Partnerships

• Develop and execute GPU procurement strategies.
• Establish relationships with NVIDIA, OEMs, distributors, and GPU hardware suppliers.
• Identify opportunities in both new and secondary GPU markets.
• Negotiate hardware supply agreements, pricing, delivery terms, and strategic partnerships.
• Evaluate GPU availability, pricing dynamics, hardware lifecycle, and investment opportunities.
• Build a reliable network of hardware and infrastructure partners.

2. AI Infrastructure Development

• Lead the planning and deployment of GPU computing infrastructure.
• Identify and evaluate data center locations, colocation providers, and infrastructure partners.
• Coordinate infrastructure requirements, including power, cooling, networking, and operational capacity.
• Develop scalable infrastructure deployment models.
• Oversee project execution in collaboration with technical and operational teams.
• Optimize infrastructure economics, deployment timelines, and operational efficiency.

3. AI Compute Sales & Commercialization

• Develop the commercial strategy for GPU compute capacity.
• Identify customers requiring AI inference, GPU cloud, and high-performance computing services.
• Build relationships with AI startups, enterprises, cloud providers, and infrastructure companies.
• Negotiate short-term and long-term compute capacity agreements.
• Develop pricing strategies and commercial partnership models.
• Drive customer acquisition, revenue growth, and infrastructure utilization.

4. Business Strategy & Ownership

• Develop the AI compute business strategy and execution roadmap.
• Build financial models and evaluate investment opportunities.
• Own business unit economics, CAPEX, OPEX, and commercial performance.
• Collaborate with leadership on financing and capital allocation.
• Establish operational and commercial KPIs.
• Build and lead a team as the business scales.
• Take full accountability for business results and profitability.

Qualifications

• 2+ years of experience in AI infrastructure, GPU cloud, data centers, cloud computing, or related industries.
• Proven track record of launching, building, or scaling infrastructure-driven businesses.
• Strong understanding of GPU computing, AI infrastructure economics, and the broader AI ecosystem.
• Demonstrated experience in at least two of the following areas:
  • GPU procurement and strategic hardware partnerships.
  • AI infrastructure development and deployment.
  • GPU compute sales and commercialization.
• Strong business development and negotiation skills.
• Experience managing complex commercial agreements and strategic partnerships.
• Solid understanding of financial modeling, CAPEX, OPEX, ROI, and unit economics.
• Entrepreneurial mindset with a strong bias toward execution.
• Ability to operate independently and make decisions in a fast-moving environment.
• Fluent English

Nice to Have

• Established relationships with NVIDIA, OEMs, GPU distributors, or major hardware suppliers.
• Experience at GPU cloud providers, neocloud companies, or AI infrastructure startups.
• Background in GPU-as-a-Service (GPUaaS), AI inference, or compute marketplaces.
• Experience with high-density data centers, Bitcoin mining, or energy-intensive infrastructure.
• Experience negotiating long-term compute capacity contracts.
• Previous experience as a founder, General Manager, or business unit leader.
• Strong professional network in the San Francisco Bay Area.

• Professional growth: support for courses, conferences, and English learning (up to 100% coverage).
• Work-life fit: remote or hybrid format with flexible hours across international teams.
• Paid leave: up to 20 vacation days + 8 company holidays + 5 personal days per year
• Recognition programs: structured performance reviews and team awards.
• Team culture: retreats in international locations (for example, company apartments in Cyprus).