This is a full-stack role at a company where the product is evolving quickly and engineers have real ownership – expect the scope to grow as we do.

Build production-grade voice, browser, document, and workflow agents that move personal injury cases forward.

Design long-horizon agent systems - including context, tools, memory, permissions, structured outputs, and human-in-the-loop controls.

Own the eval flywheel: turn real cases and operator feedback into benchmarks that continuously improve agent quality.

Optimize performance through model selection and routing, context engineering, prompting, tool design, and agent observability.

Make agents reliable across calls, documents, communications, third-party portals, partial failures, and changing case information.

Evaluate advances in agentic AI and rapidly ship the ones that improve quality, speed, or cost.

Who We Have in Mind

This role is for technical team members who want ownership over outcomes - here's what we think that requires.

3+ years building reliable, secure software in production, with the ability to own systems across the stack.

Experience shipping AI-powered products or agents beyond the prototype stage.

Experience designing practical evals and using them to understand agent behavior, compare approaches, and improve task-completion quality.

Member of Technical Staff, Applied AI

Responsibilities