Enterprise AI Deployment Engineer for Frontier Models

scalr; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

scalr, a frontier AI company, is expanding its Forward Deployed Engineering team in New York and San Francisco. You will work directly with enterprise customers to design and deploy production AI systems around frontier models, writing production-grade code alongside customer teams.

The role emphasizes hands-on delivery, ownership from discovery to deployment, and close collaboration with product and research to feed learnings back into the platform.

Qualifications

• Hands-on, customer-facing technical role required.
• Track record of shipping production software with direct customer deployments.
• Strong Python skills for building and debugging production systems.
• Good understanding of the LLM stack, including model serving and fine-tuning workflows.
• Experience with cloud infrastructure (AWS, Azure or GCP) and GPUs.
• Excellent communication, able to discuss with executives and engineers.

Responsibilities

• Work directly with enterprise customers to scope, build and deploy AI systems in their production environments
• Write production code alongside customer engineering teams, rather than just advising them
• Build agentic systems, tool-use workflows and integrations on top of frontier models
• Fine-tune, serve and optimise models for real customer workloads
• Lead technical discovery with executives, then work closely with engineers to deliver the solution
• Feed what you learn from customer deployments back into product and research

Skills

Python

Production software shipping

Customer-facing experience

LLM stack understanding

Cloud infrastructure (AWS/Azure/GCP)

Model serving & fine-tuning

Strong communication

Job description

scalr, a frontier AI company, is expanding its Forward Deployed Engineering team in New York and San Francisco. You will work directly with enterprise customers to design and deploy production AI systems around frontier models, writing production-grade code alongside customer teams.

The role emphasizes hands-on delivery, ownership from discovery to deployment, and close collaboration with product and research to feed learnings back into the platform.