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San Francisco, California, United States
Onsite
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
No one builds the AI infrastructure stack alone. The GPU makers, cloud and datacenter providers, model labs, and enterprise platforms we work with are core to how we reach customers and how we ship. The partnerships that matter in this industry are not logos on a slide — they are shipped integrations, field teams that can actually sell and support a joint solution, and customers who win because both companies showed up together. Very few people know how to make those partnerships real at the technical and commercial level simultaneously.
You will own our most strategic technical alliances end to end: NVIDIA, hyperscalers, neoclouds, datacenter operators, and the next wave of partners across models, tooling, and enterprise. You will be the person a partner's engineering, product, and field teams trust to turn a signed MOU into something that moves pipeline and ships product.
The work sits at the intersection of technical depth and commercial execution. You will go deep enough on GPUs, networking, distributed training, and inference stacks to hold your own with partner engineers, and broad enough to run joint go-to-market, executive relationships, and a scalable partner program. You will scope proofs of concept with joint customers, build the enablement that lets partner sellers position us, secure marketplace and co-sell motions, and bring partner roadmaps back into our product and research decisions.
The partnerships you build will directly shape how Prime Intellect reaches the labs, enterprises, and research teams building on our stack — and how fast we can deliver compute, training, and environments to them.
Partner Relationship Management
Own 3–5 tier-1 technical partnerships (e.g., NVIDIA, hyperscalers, neoclouds, datacenter operators) as the single accountable lead
Build relationships across the partner org at every level: alliance managers, developer relations, product and engineering, field sales, and executives
Run quarterly business reviews and set joint annual plans with clear goals, owners, and metrics
Navigate partner programs (e.g., NVIDIA Inception, NPN, cloud marketplace and co-sell programs) to unlock credits, benefits, tiering, and visibility
Negotiate and manage partnership agreements, MOUs, and joint commitments with Legal and Finance
Joint Customer Engagement
Lead and join joint customer calls with partner account teams, from discovery through technical deep dives and close
Act as the technical bridge in deals: map customer workloads to the joint solution, scope proofs of concept, and remove blockers
Coordinate escalations across both companies when joint customers hit issues
Build a pipeline of partner-sourced and partner-influenced opportunities, and report on it
Technical Integration & Product Feedback
Drive joint technical work: integrations, benchmarks, validated configurations, certifications, and optimizations on partner hardware and software
Get early access to partner roadmaps, hardware, and SDKs, and translate them into product opportunities for us
Bring partner and customer feedback into our product and research roadmaps, and advocate for our needs in the partner's roadmap
Write or co-author reference architectures, technical blog posts, and solution briefs
Training & Enablement
Build enablement content for partner field teams: pitch decks, battlecards, demo scripts, reference architectures, and FAQs
Deliver live and recorded training to partner sellers, solution architects, and support engineers so they can position, sell, and troubleshoot our products
Enable our own team on partner products, roadmaps, and programs
Track enablement reach and impact: people trained, certified, and actively co-selling
Joint Go-to-Market & Marketing
Plan co-marketing: launches, case studies, webinars, joint press, and partner showcase placements
Represent Prime Intellect at partner events and industry conferences (e.g., NVIDIA GTC), including talks, booths, and customer meetings
Secure marketplace listings and co-sell motions with cloud and channel partners
Partner Program & Strategy
Identify and evaluate new strategic partners across compute, models, tooling, and enterprise
Design a scalable partner program: tiers, benefits, onboarding, and playbooks
Own partnership metrics and report regularly to leadership on revenue impact, pipeline, and technical milestones
7+ years in technical partnerships, alliances, solutions architecture, or technical business development, with at least 3 years managing strategic partners
Direct experience working with NVIDIA, a hyperscaler (AWS, GCP, Azure), or a GPU cloud provider — ideally on the partner side of that relationship
Strong technical grounding in AI infrastructure: GPUs and accelerators, networking (InfiniBand, RoCE), distributed training and inference, and the CUDA and PyTorch ecosystem
A track record of co-selling — you've run joint customer calls and closed or influenced deals alongside partner field teams
Experience building and delivering technical enablement to sales and engineering audiences
Comfortable presenting to executives, engineers, and conference audiences
Able to run a complex, multi-stakeholder relationship with little oversight, and to say no when a joint initiative isn't worth it
Clear, concise writer: plans, briefs, and technical docs
High ownership — you see gaps and build the fix before anyone asks
AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster
Bonus:
Prior experience inside NVIDIA's partner or developer ecosystem, or inside a hyperscaler's AI/ML partner organization
Hands-on background as a solutions architect or ML engineer before moving into partnerships
Experience standing up a partner program from scratch at an early-stage infrastructure company
Existing relationships with alliance, field, and engineering teams at major compute providers
The AI infrastructure ecosystem is being assembled right now, and the partnerships that define it are still being written. You'll own the relationships that determine how Prime Intellect reaches the market, work directly with leadership and the engineering team on what we build and with whom, and sit in the room with partner executives and engineers at the companies shaping the next decade of compute. The network and expertise you build here are increasingly rare and valuable across the industry.
Cash compensation range of $250–300k + meaningful equity
San Francisco or New York, with travel to partner sites, customer meetings, and conferences (about 25–30%)
Visa sponsorship and relocation support
Professional development budget
Team off-sites and conferences
A front-row seat to building the infrastructure layer for open AI
