AI Field Engineer – Enterprise

AI Field Engineer – Enterprise

Full-Time | Hybrid / Remote-Friendly | San Mateo, CA or New York, NY
Base Salary: $176K–$224K | OTE: $220K–$280K + Equity
3+ Years Experience

Build Production AI With Enterprise Customers

We’re looking for an AI Field Engineer / Forward Deployed Engineer (FDE) to help enterprise customers move from GenAI experimentation to production-scale AI systems. You’ll combine hands-on engineering with customer-facing technical leadership—owning discovery, POCs, evaluations, deployment, and production integrations.

This is a strong fit for engineers with experience across LLM inference, open-source models, GPU infrastructure, Kubernetes, fine-tuning, and enterprise AI deployments who can communicate effectively with both ML engineers and executive stakeholders.

What You’ll Do

• Lead technical discovery, architecture discussions, POCs, load testing, and model evaluations.
• Build and deploy production AI/LLM integrations inside customer environments.
• Advise enterprise teams on LLM selection, inference architecture, fine-tuning, evaluation, and deployment.
• Work hands-on with vLLM, SGLang, TensorRT-LLM, Kubernetes, GPUs, and cloud infrastructure.
• Apply fine-tuning approaches including SFT, DPO, and RFT.
• Navigate enterprise security reviews, procurement, infrastructure constraints, champions, and technical stakeholders.
• Partner with sales to influence technical strategy and accelerate enterprise deals.
• Feed customer deployment patterns and technical requirements back into product and engineering.

Must-Have Qualifications

• 3+ years in customer-facing AI/ML engineering, Field Engineering, Forward Deployed Engineering, Applied AI, Solutions Architecture, ML Engineering, or similar.
• Proven experience shipping production AI/ML code within customer environments.
• Strong hands-on LLM inference and/or training experience with open models.
• Experience with one or more vLLM, SGLang, or TensorRT-LLM.
• Strong Python and Kubernetes skills.
• Experience with GPU optimization / LLM workloads.
• Experience with SFT; DPO/RFT is a strong plus.
• Cloud experience with AWS, Azure, or GCP.
• Strong enterprise communication and executive presence.
• Ability to translate complex AI architecture and performance trade-offs for both technical and executive audiences.
• Willingness to travel domestically to enterprise customers as needed.

Not a Fit If You Have Only…

• Built applications around closed-model APIs without hands-on open-model inference or fine-tuning.
• Provided AI strategy/advisory services without shipping production systems.
• Worked exclusively in software engineering without meaningful customer-facing or pre-sales experience.

Core Technologies

Python · LLM Inference · Open-Source LLMs · vLLM · SGLang · TensorRT-LLM · Kubernetes · GPUs · AWS · Azure · GCP · LLM Fine-Tuning · SFT · DPO · RFT · MLOps · AI Infrastructure · GenAI · Model Evaluation

Compensation & Benefits

• $176K–$224K base salary
• $220K–$280K OTE
• Quarterly performance-based variable compensation
• Competitive equity
• Above-range packages considered for highly experienced candidates
• H-1B transfer and TN sponsorship available; O-1 considered case-by-case
• US-based, remote-friendly
• Offices in San Mateo, CA and New York, NY
• Hybrid schedule for employees near an office hub
• Regular customer-site travel as required