AI Field Engineer – Enterprise

AI Field Engineer – EnterpriseFull-Time | Hybrid / Remote-Friendly | San Mateo, CA or New York, NYBase Salary: $176K–$224K | OTE: $220K–$280K + Equity3+ Years ExperienceBuild Production AI With Enterprise CustomersWe’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 DoLead 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 Qualifications3+ 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 TechnologiesPython · 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 EvaluationCompensation & Benefits$176K–$224K base salary$220K–$280K OTEQuarterly performance-based variable compensationCompetitive equityAbove-range packages considered for highly experienced candidatesH-1B transfer and TN sponsorship available; O-1 considered case-by-caseUS-based, remote-friendlyOffices in San Mateo, CA and New York, NYHybrid schedule for employees near an office hubRegular customer-site travel as required