Member of Technical Staff, Applied AI

Explore life at Finch for more.

A note from Ben

Hey, I’m Ben, CTO at Finch. I’m hiring engineers who can (a) understand what needs to be built and why, (b) ship quality work fast, and (c) own the outcomes tied to measurable legal impact.

We have an exceptionally talented group of high-personality, collaborative engineers. Nothing matters more to me than keeping that true as we grow.

The three reasons engineers generally come to (and stay at) Finch are:

1. High ownership and freedom to build. We give you a problem-space and lots of room to shape the product solution.

2. Meaningful impact and a tight feedback loop. Your work supports real people through difficult moments in their life (i.e. personal injury cases), and you sit next to users.

3. Applied AI work and room to experiment. We are building at the cutting edge of legal AI application.

If this sounds exciting, please apply.

What you'll do

Personal injury law is full of repetitive tasks, paper-based bottlenecks, and fragmented data. As a Member of Technical Staff, Applied AI, you’ll build agents that move cases forward and make those workflows dependable. You’ll own critical features end-to-end, ship fast, and work directly alongside strategy & operations, product, design, and legal teammates in a codebase where your decisions matter from day one.

• 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, and third-party portals, including when systems fail or case information changes.

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

What will make you successful

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

You’ll likely thrive if you have

• 2+ years of experience 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.

• Proficiency in Python and comfort working with React, LLM APIs, and agent frameworks.

• Strong instincts for agent design, including context construction, model selection, tool boundaries, structured outputs, failure recovery, and human handoffs.

• A track record of turning ambiguous, real-world workflows into simple, dependable systems.

• An experimental mindset: you move quickly, measure what matters, and care more about whether an agent completes the job correctly than whether the approach is clever.

It’s a plus if you have

• Experience with Pydantic AI or another production agent framework.

• Experience building voice agents, browser agents, or long-running workflow agents.

• Familiarity with Django, React, Temporal, Playwright, or AWS.

• Experience building evaluation systems, agent observability, model routing, or human-in-the-loop review tools.

• Familiarity with legal tech, healthcare workflows, document processing, or other operationally complex domains.

• You prefer a role where the roadmap, process, and success metrics are already defined.

• You are looking for a narrow remit rather than meaningful ownership across a fast-moving team.

• You’re looking for a remote-first role. We work together in our NYC office four days a week.

What happens next

We aim to run a human, efficient process. That generally includes:

1. Intro: An initial conversation about your background, motivation, and the role.

2. Technical interview: A practical, technical session with an engineer.

3. Onsite: A visit to our NYC office to interview, meet the team, and have lunch.