AI Field Engineer, Enterprise

About the role

The job suits an engineer who can write production code inside a customer's own environment and still hold a room with a VP. Work spans proof-of-concept builds, model selection and deployment patterns that feed back into the product.

At a glance

What you will do

• Lead technical discovery calls, scope proofs of concept, and run load tests and evaluations to pick model architecture and deployment setup
• Manage several stakeholders per account and pass recurring pain points back to the product roadmap

What they look for

• 4 or more years of experience, with deep hands-on work in LLM inference or training
• Knowledge of open-model frameworks such as vLLM, SGLang or TensorRT-LLM and fine-tuning workflows like SFT
• A record of shipping production code in a customer's environment, not just advising
• Strong Python plus GPU and cloud infrastructure experience on AWS, Azure or GCP, and comfort with Kubernetes
• Pre-sales or customer-facing field engineering background, and ease presenting trade-offs to both ML engineers and executives
• Willingness to travel domestically to enterprise customers

Nice to have

• Hyperscaler experience in an AI capacity
• Prior client-facing AI or ML roles such as solutions architect or applied AI engineer