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Prime Intellect is seeking a Founding Solutions Architect to lead technical discovery and architecture for AI workloads, ensuring the company becomes the technical winner in every deal.
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.
Responsibilities
- Technical Discovery & Architecture
- Benchmarks, POCs & the Technical Business Case
- Playbooks & Platform Adoption
What We're Looking For
- Strong ML infrastructure, distributed systems, cloud, or GPU-compute background
- Working knowledge of modern training and inference stacks, CUDA/GPU environments, and model-serving patterns
- Customer-facing experience in solutions architecture, sales engineering, forward-deployed engineering, or a similar role
- Ability to communicate fluently with both ML engineers and executive stakeholders — and to know which conversation you are in
- A strong bias toward proving claims with real customer workloads and benchmarks rather than slides
- 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: Hands-on experience running or optimizing large-scale distributed training (FSDP, Megatron, DeepSpeed, or similar) or high-throughput inference (vLLM, SGLang, TensorRT-LLM)
- Experience benchmarking across hardware generations (H100, H200, GB200) and interconnects (InfiniBand, RoCE)
- Background at a GPU cloud, neocloud, hyperscaler AI team, or frontier lab infrastructure team
- Experience building a solutions or forward-deployed function from scratch
What We Offer
- Cash compensation range of $250–$320k + meaningful equity
- Flexible work (remote or San Francisco), with travel to customer sites as needed
- 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