AI Field Engineer - Enterprise
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 5d ago
The date the source published, not the day we noticed it (2026-10-28). Last seen at its source 3h ago.
We have tracked this listing since 28 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$176k–224k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workable employer's own board first seen 5d ago · last seen 3h ago
The listing
About the Company
Our 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 Role
Embed 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 Do
Lead 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.
Requirements
What We Are Looking For
Three 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.
Benefits
Compensation and Benefits
$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.
Location and Work Model
Full-time and remote, with a preference for candidates near San Francisco or New York City. Domestic travel to enterprise customers as needed.