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San Francisco, California, United States
Hybrid
Available
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.
This role sits at the intersection of customer success, technical operations, and AI infrastructure delivery. You will work directly with customers to help them onboard, deploy, and scale on Prime Intellect infrastructure, while also building the internal systems, workflows, and automation that make that experience scalable over time.
Beyond supporting individual accounts, this person will help define how Prime Intellect serves sophisticated technical customers: turning high-touch support and deployment work into repeatable processes, better tooling, and durable operational leverage.
Serve as a primary point of contact for customers running AI workloads on our infrastructure
Own customer onboarding and deployment coordination from post-sale through production readiness
Build trusted relationships with customer teams and proactively manage issues, risks, and escalations
Partner with engineering and operations to ensure customer needs are translated clearly into internal action
Build and improve the internal systems that support customer onboarding, deployment tracking, escalation management, and account health
Identify repetitive manual workflows and turn them into streamlined processes, tooling, or automation
Help define the operating cadence, support infrastructure, and service model for managing technical customer accounts at scale
Create structure where none exists today, improving both customer experience and internal efficiency as the business grows
Track billing, contract milestones, renewals, and other key account workflows
Maintain visibility into deployment timelines, infrastructure commitments, and customer-specific requirements
Coordinate across customers, finance, engineering, and leadership to keep accounts running smoothly end-to-end
2–5 years of experience in customer success, technical account management, operations, or a similar cross-functional role
Strong interest in AI, GPU infrastructure, cloud systems, or technical products serving sophisticated customers
Comfortable working directly with customers and internal technical teams
Highly organized, detail-oriented, and able to manage multiple workstreams at once
Strong written and verbal communication skills
High ownership and willingness to operate flexibly when customer needs require urgency
Energized by building processes from the ground up in a fast-moving environment
Experience with infrastructure, cloud, DevOps, or enterprise technical products
Familiarity with SLAs, support operations, billing, procurement, or contract administration
Exposure to AI/ML infrastructure, model training environments, or GPU-based products
Experience in startups or high-growth environments
$200-275k Cash compensation + equity incentives
Flexible work environment
Visa sponsorship and relocation support
Professional development budget
Team off-sites and conference attendance
