AI Field Engineer, AI infrastructure (Remote - US)
$220,000–$280,000 year
RemoteUnited States
Job Summary
Run the full pre-sales field cycle, including discovery, POC scoping, model evals, and final model selection. Ship real production code inside customer environments by deploying and fine-tuning open-model LLMs using frameworks like vLLM, SGLang, and TensorRT-LLM. Act as a true partner to your sales counterpart, shaping deal strategy and building relationships across a customer's org from engineers to executives. Own the technical win from the first discovery call all the way through production for Fortune 500 enterprises and AI-native startups. This forward-deployed engineering role requires full-time work history with openness to travel to enterprise customers as needed.
Required Qualifications
- 3+ years in a client-facing AI/ML role
- Real hands-on experience with open-model LLM inference and/or fine-tuning
- Hyperscaler experience in an AI context (AWS, Azure, or GCP)
- Strong Python skills
- Comfort with GPU infrastructure and Kubernetes
- A background at an AI-native company or a SaaS company genuinely building AI features
- Full-time work history
- Openness to travel to enterprise customers as needed
- Remote-friendly with hubs in New York and San Mateo
- Flexibility to work from anywhere in the US
- Regular travel to enterprise customers
- Open to visa transfers (e.g. OPT, H1B transfers)
- Open to visa sponsorships (e.g. new H1B, TN)
- Base salary $176K–$224K
- OTE $220K–$280K
- Performance-based variable compensation
- Comprehensive benefits package
Desired Qualifications
- DPO/RFT
- Experience with vLLM
- Experience with SGLang
- Experience with TensorRT-LLM
- SFT baseline
- Experience at an AI-native company or a SaaS company genuinely building AI features (not bolting them on)
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