AI Field Engineer, AI Infrastructure (Remote - US)

Our client is a fast-scaling AI infrastructure company that helps enterprises and AI-native startups build, fine-tune, and serve their own specialized AI models — no more relying on someone else's black-box API. Their platform runs in production for some of the most recognizable names in tech, spanning text, image, embedding, audio, and multimodal workloads. Freshly backed by a Series D at a $17.5B valuation, this is a company with real scale, real customers, and real momentum behind it.

They believe the next generation of great products will be built by companies that own their AI stack, not just rent it. Their mission is making open-model AI infrastructure genuinely fast, flexible, and production-grade for the teams building at the frontier.

This is a forward-deployed engineering role where you're never far from either a terminal or a whiteboard with a VP on it. You'll work directly with VP Engineering, Head of AI/ML, and CTO-level partners at Fortune 500 enterprises and cutting-edge AI-native startups, owning the technical win from the first discovery call all the way through production. Two tracks are open — Enterprise and AI-Native — same role, different customer base, and we'll talk through which fits your background and interests best.

Run the full pre-sales field cycle yourself: discovery, POC scoping, model evals, and final model selection

Ship real production code inside customer environments — this is hands-on building, not advisory slides

Deploy and fine-tune open-model LLMs using frameworks like vLLM, SGLang, and TensorRT-LLM (SFT baseline, DPO/RFT a big plus)

Act as a true partner to your sales counterpart, shaping deal strategy rather than just supporting it