AI Field Engineer - Enterprise

Raydar

7d•$176,000 - $224,000•Remote

About The Position

Embed with the company’s enterprise customers to turn complex generative AI challenges into production systems. The role combines hands-on engineering with executive presence to build customer trust and drive deals from initial discovery through production. It is full-time and remote, with a preference for candidates near San Francisco or New York City. Domestic travel to enterprise customers is required as needed.

Requirements

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 sufficient.
Experience shipping production code inside a customer’s environment, not just providing advisory work.
Strong Python, GPU, and cloud infrastructure experience (AWS, Azure, or GCP), and comfort with Kubernetes.
Executive presence, with the ability to lead a technical deep dive with an ML engineer and present trade-offs to a VP.
Pre-sales ownership from discovery through proof-of-concept scoping, evaluations, and model selection.

Nice To Haves

Candidates located near San Francisco or New York City are preferred.

Responsibilities

Lead technical discovery calls, scope proofs of concept, and run load tests and evaluations to select model architectures and deployment configurations.
Build end-to-end proofs of concept and production integrations hands-on in customer environments, working within infrastructure and security constraints.
Advise customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation frameworks.
Manage multi-stakeholder enterprise relationships and move deals forward.
Feed recurring customer pain points back into the product roadmap.