harvey

Senior Software Engineer, Agents

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At a Glance

Location
New York, United States
Employment
FULL_TIME
Experience
5–8 years
Compensation
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Department
Harvey
Posted
2026-07-22

Key Requirements

Required Skills

Python

Domain Knowledge

  • Engineering
  • Finance
  • Legal

Requirements

Passion for building effective domain-specific agents.

Iterative mindset: you develop proof of concepts, make decisions quickly, and ship v0s.

Comfortable with when and how to use evaluations to drive quality.

Humble and adaptable about code and frameworks.

We expect you to drive adoption of new best practices as they develop.

5-8 years (post-BS/MS) of software engineering experience.

Compensation & Benefits

$193,400 - $290,000 USD

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Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

Responsibilities

As a Software Engineer, Agents, you'll build the systems that make our AI agents indispensable to legal professionals.

You will design environments and actions for agentic professional work, make model selection decisions, manage context windows, create optimal tools, and develop evals that enable faster iteration loops to unlock new capabilities.

We're looking for engineers and researchers who are immersed in the space, driven to ship impactful products, and are experienced in using practical evaluations to drive task completion quality and customer delight.

Partner with customers and PMs to understand legal workflows, design practical evaluations that capture what “excellent” means, and ship agents that get the job done.

Optimize agent performance through prompt engineering, model selection, tool design, skill writing, context window management, and eval harness development.

Work with our model infra team to design and implement infrastructure for low-latency agent execution, including caching strategies, parallel tool calls, or subagent patterns.