Applied AI Engineer - Build Self-Improving Agent Systems

judgmentlabs; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

judgmentlabs is seeking Applied AI Engineers to build AI systems that use agent interaction data to understand, evaluate, and improve agent behavior at scale. You'll work with real-world data, apply frontier production methods, and ship your work into the product.

You will own projects end-to-end with autonomy and collaborate with teams across finance, legal, and operations on high-stakes workflows. Collaborate with external companies and research partners on frontier AI research to push the

Qualifications

• Agency: intellectually curious, self-directed, up-to-date with research trends.
• Depth of thought: reason clearly about abstract systems; RL experience preferred.
• Ownership: own outcomes and drive impact beyond tasks.

Responsibilities

• Build AI systems to aggregate, index, and analyze large-scale long-running agent interaction data.
• Design post-training and optimization workflows to improve agents.
• Build agent platform infrastructure, including orchestration, runtimes, and developer tools.
• Build internal tools and infrastructure to support rapid experimentation, analysis, and training.
• Work closely with product to integrate agents into customer-facing workflows.
• Collaborate with external companies and research partners on frontier AI research.

Skills

Agency

Depth of thought

Ownership

Job description

judgmentlabs is seeking Applied AI Engineers to build AI systems that use agent interaction data to understand, evaluate, and improve agent behavior at scale. You'll work with real-world data, apply frontier production methods, and ship your work into the product.

You will own projects end-to-end with autonomy and collaborate with teams across finance, legal, and operations on high-stakes workflows. Collaborate with external companies and research partners on frontier AI research to push the