AI Field Engineer

Job Description

Job Description

AI Field Engineer

We're a well-funded AI infrastructure company building the platform that lets teams run, tune, and scale AI on open models in production. Our infrastructure powers high-scale production workloads for leading technology companies. We're hiring AI Field Engineers — the technical tip of the spear who embed with our most ambitious customers to turn complex AI problems into production systems, fast.

This role sits at the intersection of engineering, product, and customer delivery. You'll be hands-on-keyboard building POCs, MVPs, and production integrations, while holding your own in executive-level conversations about architecture, strategy, and business outcomes.

What You'll Do

• Build POCs, MVPs, and production integrations directly inside customer codebases.
• Own customer accounts end to end — manage relationships, run discovery, and present to stakeholders.
• Handle deployment and performance engineering across customer environments.
• Partner with Product to channel customer feedback into platform improvements.

What We're Looking For

• 5–10 years in customer-facing ML/AI engineering (Forward Deployed, Applied AI, or Solutions Engineering) as a senior IC — roughly 60% hands-on coding/deployment, 40% client engagement and product feedback.
• Track record building and shipping production ML/AI systems from the ground up.
• Direct client-facing engineering experience — running POCs/MVPs, managing accounts, and presenting to stakeholders.
• Strong Python and hands-on ML/AI engineering depth.
• A history of collaborating with Product to turn client feedback into shipped improvements.
• Low ego, extreme ownership.
• Comfortable with regular on-site customer visits.

Nice to Have

• Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and cloud GPU infrastructure (AWS, GCP, Azure).
• Familiarity with Kubernetes.
• Background at an AI/ML startup or infrastructure company, a professional services firm, or big tech with client-facing exposure.

Tech Stack

Python, vLLM, SGLang, TensorRT-LLM, Kubernetes, AWS, Azure, GCP, Azure AI Foundry, AWS Bedrock, AWS SageMaker, GCP Vertex AI, LLM fine-tuning (SFT, DPO, RFT), GPU infrastructure.

Compensation & Logistics

• Base salary $176K–$228K (OTE $220K–$285K) plus competitive equity.
• Location: New York, NY or San Mateo, CA; open to remote within the US.
• Regular on-site customer travel expected.
• Visa sponsorship: H-1B transfers and TN visas sponsored; O-1 considered case-by-case.
• Full-time.

Interview Process

1. Recruiter screen (30 min).
2. Take-home assignment, self-paced.
3. Discovery + hiring manager conversation (45 min).
4. Culture + live coding (1 hr).
5. On-site final loop (~2 hrs): customer demo/presentation + values conversation.
6. Executive interview (30 min).
7. Offer.