Head of Compute Economics & GPU Infrastructure

Cognichip; Redwood City (CA); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Early-stage equity

Competitive compensation package

Collaborative culture

Job summary

Cognichip in Redwood City seeks a Director of Infrastructure Operations to own GPU capacity planning, compute economics, and long-range infrastructure strategy, bridging Finance and Engineering to build end-to-end economic models and investment decisions.

You will drive CapEx/OpEx, develop dashboards, and align infrastructure with business goals while collaborating with Finance, Engineering, and leadership to unlock scalable AI compute.

Qualifications

• Experience in data-center economics, capacity planning, or cost engineering.
• Strong understanding of unit economics, CapEx/COGS modeling, and depreciation.
• Advanced modeling in Excel or Google Sheets.

Responsibilities

• Lead multi-year GPU capacity planning and demand forecasting.
• Build fully loaded cost models and unit-economics metrics for compute infrastructure.
• Evaluate buy/lease/cloud infrastructure decisions and build supporting business cases.
• Translate capacity needs into CapEx/OpEx and cost-of-goods impacts.
• Partner with Finance on operating plans and long-range forecasts.
• Build models and dashboards for capacity, utilization, and cost visibility.
• Serve as the key liaison between Engineering and Finance on infrastructure economics.

Skills

Data-center economics

Capacity planning

Cost engineering

Excel/Sheets modeling

Finance liaison

Education

Bachelor’s degree in Economics/Engineering/Computer Science/Operations Research

Tools

Google Sheets

Job description

Cognichip in Redwood City seeks a Director of Infrastructure Operations to own GPU capacity planning, compute economics, and long-range infrastructure strategy, bridging Finance and Engineering to build end-to-end economic models and investment decisions.

You will drive CapEx/OpEx, develop dashboards, and align infrastructure with business goals while collaborating with Finance, Engineering, and leadership to unlock scalable AI compute.