Staff Software Engineer, Agents

Harvey

$231K — $340K *
Legal & Accounting
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of software engineering experience, preferably post-BS/MS.
  • Proficiency in Python with experience in LLM APIs and agent frameworks.
  • Experience in shipping user-facing products, backend or full-stack.
  • Passionate about building effective domain-specific agents.
  • Comfortable using evaluations to enhance product quality.
  • Iterative mindset focused on developing and shipping prototypes quickly.
  • Adaptable to evolving code and frameworks, driving best practices.

Responsibilities

  • Partner with customers and PMs to understand legal workflows and design evaluations for quality.
  • Optimize agent performance through various techniques like prompt engineering and tool design.
  • Collaborate with the model infra team to implement low-latency execution infrastructure.
  • Enhance observability and instrumentation to identify performance bottlenecks.
  • Stay updated on developments in agentic systems and integrate learnings into product development.

Benefits

  • Flexible work environment to accommodate remote work.
  • Opportunities for professional development and growth within the field.
  • Access to cutting-edge tools and technologies in AI and legal tech.
  • Engaging and impactful projects that directly influence legal practices.
Full Job Description
Role Overview

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.

Representative Projects
  • Save weeks of effort on high pressure M&A deals by automating information requests and diligence checks across hundreds of thousands of files with retrieval and file editing agents.
  • Dramatically speed up deal turnaround speed by improving the latency and quality of agents on applying a standard legal "playbook" to contracts.
  • Ensure that our clients win their complex, data-hungry litigation cases by optimizing our multi-source retrieval agents.
  • Enable board-ready PowerPoint generation by tuning the harness and libraries for coding agents.


What You'll Do
  • 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.
  • Improve our observability and instrumentation to profile agent behavior, identify bottlenecks, and drive optimization decisions.
  • Stay current on new developments in agentic systems and bring those learnings back to the products we build.


What You Have
  • 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.
  • 8+ years (post-BS/MS) of software engineering experience.
  • We are hiring for this role across Mid, Senior, and Staff levels.
  • Proficiency in Python and experience working with LLM APIs and agent frameworks.
  • Experience with shipping user-facing products, either on the backend or full-stack.


Compensation Range

$231,000 - $340,000 USD

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