JOB-2003
Our client is a fast-growing generative-AI infrastructure company whose platform serves open models to businesses. It wants a field engineer to embed with its most ambitious enterprise accounts and convert complicated generative-AI needs into live production systems. The role combines practical engineering skill with the poise to earn trust inside large organizations and carry opportunities all the way to deployment.
Responsibilities
- Run technical discovery calls, scope proofs of concept, and carry out load testing and benchmarking to select a suitable model design and serving setup for each customer
- Build proofs of concept and production integrations from start to finish inside customer environments, working within their infrastructure and security constraints
- Advise on model choice, on fine-tuning approach (SFT, DPO or RFT), and on how to evaluate results as customers move from experimenting with open models to production
- Manage relationships across many stakeholders: find technical champions and align the right people to keep deals moving
- Relay recurring customer frustrations and rollout patterns to the product team
Profile
- Three or more years in client-facing AI/ML roles such as solutions architecture, forward-deployed engineering, applied AI or sales engineering
- Substantial practical background in serving or training large language models with open-model tooling such as vLLM, SGLang or TensorRT-LLM, plus supervised fine-tuning
- A record of deploying working production software within a client’s own environment
- Strong Python plus GPU and cloud infrastructure work on platforms such as GCP, Azure or AWS, and ease with Kubernetes
- Able to hold an engineering-level deep dive and an executive briefing on the same day
- Willing to travel domestically to customers as needed
Remote within the United States. Visa transfers are considered.
