AI Field Engineer (Enterprise) - Generative AI Deployment & Customer Success

AI Field Engineer (Enterprise)

📍 Location: San Mateo, CA / New York, NY (Hybrid, Remote-Friendly within the US)

💼 Employment Type: Full-Time

💰 Compensation: $176,000 - $224,000 Base Salary + OTE $220,000 - $280,000 + Equity

About the Role

We are seeking an experienced AI Field Engineer to work directly with enterprise customers and help transform complex Generative AI use cases into production-ready systems. This role combines hands-on AI engineering expertise with customer-facing responsibilities, partnering closely with enterprise stakeholders from discovery through deployment.

The ideal candidate has experience deploying AI/ML solutions in customer environments, working with open-source LLMs, inference infrastructure, fine-tuning workflows, and enterprise-scale deployments.

Responsibilities

- Lead technical discovery sessions with enterprise customers.

- Scope and execute Proofs of Concept (POCs), evaluations, and load testing.

- Build and deploy AI-powered solutions directly within customer environments.

- Advise customers on model selection, deployment architecture, and fine-tuning strategies.

- Work closely with customer technical teams, executives, and stakeholders.

- Navigate enterprise security reviews, infrastructure requirements, and procurement processes.

- Provide product feedback based on customer needs and deployment patterns.

Required Qualifications

Experience

- 3+ years of experience in AI/ML field engineering, solutions architecture, applied AI, ML engineering, infrastructure engineering, or similar customer-facing technical roles.

- Experience shipping production AI/ML systems in customer environments.

- Experience leading technical engagements from discovery through deployment.

- Background in AI infrastructure, MLOps, developer platforms, or AI-enabled enterprise software.

Technical Skills

- Strong Python programming skills.

- Hands-on experience with Kubernetes.

- Experience with LLM serving frameworks such as:

- vLLM

- SGLang

- TensorRT-LLM

- Experience with model fine-tuning methodologies:

- SFT

- DPO

- RFT (preferred)

- Knowledge of GPU optimization and LLM inference performance.

- Experience with cloud platforms:

- AWS

- Azure

- GCP

Professional Skills

- Strong communication and executive presentation skills.

- Ability to work with both technical and executive stakeholders.

- Experience managing complex enterprise customer relationships.

- Comfortable traveling domestically as needed.

Preferred Qualifications

- Experience with open-source LLM deployment and optimization.

- Experience with AI infrastructure platforms and MLOps tooling.

- Experience building production-grade GenAI applications.

Tech Stack

Python • Kubernetes • vLLM • SGLang • TensorRT-LLM • AWS • Azure • GCP • AWS Bedrock • AWS SageMaker • Azure AI Foundry • Vertex AI • GPU Infrastructure • Open-Source LLM Frameworks

Compensation & Benefits

- Base Salary: $176K - $224K

- OTE: $220K - $280K

- Quarterly performance-based variable compensation

- Competitive equity package

- Visa Sponsorship Available (H-1B Transfers, TN; O-1 considered case-by-case)

- Remote-Friendly within the United States

- Hybrid schedule for employees located near office hubs

Apply Now

If you're passionate about AI infrastructure, enterprise deployments, and helping customers successfully adopt Generative AI at scale, we'd love to hear from you.