AI Field Engineer - Enterprise Series D AI inference platform $176k to $224k USD base a year Posted yesterday

# AI Field Engineer - EnterpriseSeries D AI inference platform* LocationUnited States* WorkRemote* TypeFull-time* Posted28 October 2026Apply for this roleThe role, as published## About the CompanyOur client is a Series D AI inference platform for building, tuning and scaling AI on open models. Founded in 2021, it has raised about $1.5B, has crossed $1 billion in annualized revenue and powers production workloads at some of the best-known technology companies.

The team is roughly 200 people.## About the RoleEmbed with the company's most ambitious enterprise customers and turn complex GenAI challenges into production systems. You are the technical tip of the spear, pairing deep hands-on engineering with the executive presence to earn trust across large organizations and drive deals from first discovery call to production.## What You Will DoLead technical discovery calls, scope proofs of concept and run load tests and evaluations to choose the right model architecture and deployment configuration.

Build end-to-end POCs and production integrations hands-on inside customer environments, working within their infrastructure and security constraints.

Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT) and evaluation frameworks.

Manage multi-stakeholder enterprise relationships and move deals forward quickly.

Feed recurring customer pain points back into the product roadmap.## What We Are Looking ForThree or more years in client-facing AI or ML roles such as solutions architect, forward-deployed engineer, applied AI engineer or sales engineer.

Hands-on LLM inference and fine-tuning experience with open-model frameworks such as vLLM, SGLang or TensorRT-LLM. Closed-model API work alone is not enough.

Production code shipped inside a customer's environment, not just advisory work.

Strong Python, GPU and cloud infrastructure experience (AWS, Azure or GCP) and comfort with Kubernetes.

Executive presence: you can run a technical deep-dive with an ML engineer and present trade-offs to a VP in the same afternoon.

Pre-sales ownership from discovery through POC scoping, evaluations and model selection.## Location and Work ModelFull-time and remote, with a preference for candidates near San Francisco or New York City. Domestic travel to enterprise customers as needed.## Compensation, as the posting describes it$176,000-$224,000 base salary, or $220,000-$280,000 on-target earnings, plus competitive equity. H-1B transfers and TN visas are sponsored.

Pay$176k to $224kUSD base a year