AI Factory Partnerships Lead - OEM & Infrastructure Alliances
San Francisco · 10+ years experience · Full-time · Hybrid · Posted Sep 25, 2026
At a glance
- Experience
- 10+ years experience
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- San Francisco
About Fireworks AI
- Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
About the role
- Fireworks is hiring a Partnerships Lead to collapse full-stack, on-prem and colocated AI factory deployments into a single, pre-integrated bundle.
- You will assemble alliances across OEMs and silicon, packaged with Fireworks as the operating system on top.
- You will own the bundle definition, joint pricing, and go-to-market plan end to end from first alliance conversation to repeatable revenue.
Responsibilities
- Build alliances across the stack
- Define the reference bundle with Fireworks as the serving and orchestration layer
- Validate joint architectures with Fireworks engineering
- Structure and negotiate the commercial agreements
- Build and execute the joint GTM plan including ICP, field plays, and targets
- Enable field sellers on joint offering
- Drive deals end to end with partner sellers and own the forecast
Requirements
- 10+ years in enterprise infrastructure, with at least one joint offering you built and scaled
- Key relationships inside at least two of: Dell, HPE, NVIDIA, AMD, or equivalent OEM
- Understand the AI factory stack
- Experience in integrated offerings (appliance or validated design programs)
Preferred qualifications
- Background selling into on-prem or sovereign AI deployments, where the customer runs the hardware and the vendor runs the software
- Familiarity with LLM inference economics: throughput per GPU, utilization, and why the software layer determines the ROI of the whole bundle
Skills
- PyTorch
