Head of Business, AI Infrastructure

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Location: Seattle, WA/Remote; open to candidates anywhere in the U.S.

Compensation: $250K–$400K+, depending on experience

In-Office Policy: Flexible/Remote with office space available if located in Seattle; international travel to India required


My client is building a gigawatt-scale AI infrastructure business from scratch—not just a data center, but a full compute services operation that will serve enterprises across India and beyond. Think AWS or Azure, but AI-native and purpose-built for the next decade of workloads.

We're looking for someone who can turn massive GPU infrastructure into a real business. You understand cloud economics at a deep level, you've owned a P&L, and you know how to price, package, and sell infrastructure services to enterprises. This isn't a strategy role where you make slides, you'll be building the commercial engine for one of the largest AI infrastructure investments in India, working from the US with a small, sharp team.

If you've spent time at a hyperscaler and wondered what it would be like to build that from the ground up with real backing and real scale, this is your shot.

What You’ll Do

  • Own the P&L for AI infrastructure services end-to-end: revenue, margin, unit economics, capital efficiency

  • Build pricing models and commercial structures for GPU-as-a-service, inference endpoints, dedicated clusters, and hybrid deployments

  • Define target customers and go-to-market strategy across AI startups, enterprise ML teams, research institutions, and government

  • Lead enterprise sales cycles for large infrastructure deals; you'll be in the room with CXOs making the case

  • Work with technical teams to translate customer requirements into infrastructure specs and SLAs

  • Lead calls with overseas teams to review progress, present business strategy, and align on commercial priorities

  • Track the competitive landscape: AWS, Azure, GCP AI services, plus AI-native players like CoreWeave, Lambda, and Crusoe

  • Build and lead a commercial team as the business scales

  • Travel to India periodically to work directly with infrastructure and client teams

Who You Are

  • You've owned a cloud or infrastructure services P&L, ideally $50M+ in revenue; you understand the economics of compute at scale

  • Prior experience at a hyperscaler (GCP, Azure, AWS) or major colocation/managed services provider; you know how these businesses actually work

  • Deep fluency with cloud pricing, capacity planning, consumption models, and margin structures; you can build the financial model, not just review it

  • Comfortable selling to enterprises; you've been in rooms with CXOs and closed large infrastructure deals

  • Technically fluent enough to have credible conversations about GPU architectures, networking, and AI workloads—you don't need to configure a switch, but you need to know why InfiniBand matters

  • Hungry to build something from scratch; you're not looking for a role where the playbook already exists

  • Comfortable with ambiguity; you'll be defining the business model as you go, not executing an existing one

  • Strong communicator who can translate between technical teams and business stakeholders across time zones

  • Comfortable working with global teams; you can hold a high bar while being collaborative and collegial with overseas colleagues

Nice to Have

  • Specific experience with AI/ML infrastructure (GPU clusters, training services, inference platforms)

  • Familiarity with India market dynamics: enterprise buying patterns, regulatory environment, data localization requirements

  • Background with large industrial conglomerates or sovereign-backed technology ventures

  • Existing relationships with enterprise and government buyers in emerging markets

Benefits and More

  • Competitive compensation

  • Medical and Dental benefits

  • 401K

  • Office space in Seattle with remote flexibility, we value quality candidates over location

  • Ground-floor opportunity to shape AI product strategy for 500M+ users

  • Direct reporting to leadership with minimal bureaucracy

  • Small, sharp team culture that uses AI extensively in our own work

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Head of Engineering, AI Infrastructure Engineering

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