Production AI Agent Engineer — Frontier Applied AI

Scale; Seattle, New York, San Francisco (WA, NY, CA); On-site; USD 180,000 - 225,000; Full time

Benefits offered by this job

Health coverage

Retirement benefits

Learning stipend

Generous PTO

Commuter stipend

Job summary

Scale is seeking a Frontier Agent Engineer (Applied AI) to bridge cutting-edge AI research and production deployment for enterprise customers in Seattle. You’ll design and deploy intelligent systems that combine frontier models with structured data, retrieval, and traditional ML, across diverse industries and use cases.

You will lead experiments, evaluate new models, and build production workflows with strong emphasis on reliability, safety, and cost, collaborating with infrastructure teams and

Qualifications

• 4+ years of software engineering, ML, or applied AI experience.
• Experience building production AI systems using LLMs.
• Experience with OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems.
• Strong understanding of ML fundamentals and modern language models.
• Excellent communication skills and the ability to work with enterprise customers.

Responsibilities

• Design and deploy production AI agents leveraging LLMs, retrieval, memory, and tool use.
• Architect intelligent systems combining LLMs, traditional ML, knowledge, and enterprise data.
• Develop multi-agent systems coordinating reasoning, planning, and human oversight.
• Evaluate new models and techniques; iterate from hypothesis to production rollout.
• Build rigorous evaluation pipelines including offline/online benchmarking.
• Collaborate with infra teams to deploy secure AI systems in enterprise clouds.

Skills

Production AI systems

LLMs

OpenAI/Claude/MCP

Agent frameworks

Enterprise communication

Job description

Scale is seeking a Frontier Agent Engineer (Applied AI) to bridge cutting-edge AI research and production deployment for enterprise customers in Seattle. You’ll design and deploy intelligent systems that combine frontier models with structured data, retrieval, and traditional ML, across diverse industries and use cases.

You will lead experiments, evaluate new models, and build production workflows with strong emphasis on reliability, safety, and cost, collaborating with infrastructure teams and