Frontier AI Agent Architect

FDE Times; San Francisco (CA); On-site; USD 180,000 - 225,000; Full time

Job summary

Scale AI is seeking a Frontier Agent Engineer to bridge cutting-edge AI research and production deployment. You will design, evaluate, and deploy intelligent systems that combine frontier models with enterprise data, retrieval, and traditional ML tooling to deliver scalable, reliable outcomes.

You will partner with enterprise customers across industries to architect multi-agent workflows, experiment with new models and techniques, and drive production deployments that meet business impact

Qualifications

• 4+ years of software, ML, or applied AI experience.
• Strong Python programming skills.
• Experience building production AI systems using LLMs.
• Experience with OpenAI, Claude, MCP, vector databases, or retrieval systems.
• Strong understanding of ML fundamentals and modern language models.
• Experience designing or evaluating AI systems using quantitative metrics.
• Excellent communication with enterprise customers.

Responsibilities

• Design and deploy production AI agents leveraging LLMs, retrieval, and memory.
• Architect systems combining LLMs, knowledge, and deterministic software for production workflows.
• Develop multi-agent systems coordinating reasoning, tool usage, and oversight.
• Evaluate frontier models and techniques in production settings.
• Own experimentation lifecycle from hypothesis to rollout.
• Partner with customers to translate needs into technical architectures.

Skills

Python

Production AI

LLM integration

Enterprise customer comms

ML fundamentals

Tools

OpenAI API

Claude

MCP

Vector databases

Retrieval systems

Job description

Scale AI is seeking a Frontier Agent Engineer to bridge cutting-edge AI research and production deployment. You will design, evaluate, and deploy intelligent systems that combine frontier models with enterprise data, retrieval, and traditional ML tooling to deliver scalable, reliable outcomes.

You will partner with enterprise customers across industries to architect multi-agent workflows, experiment with new models and techniques, and drive production deployments that meet business impact