Own Your Intelligence

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.

Your Role

Every serious AI team evaluating infrastructure asks the same question: will this actually run my workload better, faster, or cheaper than what I have today? Most vendors answer with slides. We want to answer with benchmarks on the customer's own workload, and then design the production architecture that delivers on them.

As our Founding Solutions Architect, your mission is to make Prime Intellect the technical winner in every deal. You will own the path from workload discovery through architecture, benchmark, proof of concept, and production design. You will sit with customers' ML engineers to understand what they are actually training and serving — GPU type, cluster requirements, networking, utilization and performance objectives — then design the right architecture on Prime infrastructure, run the POC against their baseline and the competitive alternatives, and turn latency, throughput, utilization, and cost results into a technical business case that holds up under scrutiny.

This is a founding role. There is no playbook yet for how we prove technical wins; you will write it. The benchmark methodologies, reference architectures, and POC frameworks you build will become how Prime Intellect sells to every lab and enterprise that follows.

Responsibilities

Technical Discovery & Architecture

Lead deep technical discovery across training, post-training, and inference workloads

Understand each customer's GPU requirements, cluster topology, networking, storage, utilization patterns, and performance objectives

Design customer architectures on Prime infrastructure that meet those objectives and are ready for production

Partner with engineering on migration and deployment requirements so what we design is what gets shipped

Benchmarks, POCs & the Technical Business Case

Own workload benchmarks and proofs of concept against customer baselines and competitive alternatives

Translate latency, throughput, utilization, and cost results into a defensible technical business case for ML engineers and executive buyers alike

Set the standard for benchmark quality: methodology, reproducibility, and honest comparison

Drive time to technical validation down with every deal

Playbooks & Platform Adoption

Develop repeatable benchmark and reference-architecture playbooks that scale beyond you

Support technical evaluation and adoption of Model Factory, bringing customers from compute onto the full training stack

Feed what you learn from customer workloads back into product and research priorities