Staff Software Engineer, Agents

Harvey Harvey · AI Frontier · San Francisco, CA · Engineering

Staff Software Engineer focused on building and optimizing agentic AI systems for legal professionals. Responsibilities include designing agent environments, selecting models, managing context, creating tools, developing evaluations, and improving agent performance through prompt engineering, model selection, and tool design. The role also involves working with infrastructure teams on low-latency execution and enhancing observability.

What you'd actually do

  1. 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.
  2. Optimize agent performance through prompt engineering, model selection, tool design, skill writing, context window management, and eval harness development.
  3. 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.
  4. Improve our observability and instrumentation to profile agent behavior, identify bottlenecks, and drive optimization decisions.
  5. Stay current on new developments in agentic systems and bring those learnings back to the products we build.

Skills

Required

  • 8+ years (post-BS/MS) of software engineering experience
  • Proficiency in Python
  • experience working with LLM APIs and agent frameworks
  • Experience with shipping user-facing products, either on the backend or full-stack

Nice to 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.

What the JD emphasized

  • build the systems that make our AI agents indispensable
  • design environments and actions for agentic professional work
  • make model selection decisions
  • create optimal tools
  • develop evals that enable faster iteration loops
  • immersed in the space
  • driven to ship impactful products
  • experienced in using practical evaluations to drive task completion quality and customer delight
  • automating information requests and diligence checks across hundreds of thousands of files with retrieval and file editing agents
  • improving the latency and quality of agents on applying a standard legal "playbook" to contracts
  • optimizing our multi-source retrieval agents
  • Enable board-ready PowerPoint generation by tuning the harness and libraries for coding agents
  • Partner with customers and PMs to understand legal workflows
  • design practical evaluations that capture what “excellent” means
  • ship agents that get the job done
  • Optimize agent performance
  • prompt engineering
  • model selection
  • tool design
  • skill writing
  • context window management
  • eval harness development
  • design and implement infrastructure for low-latency agent execution
  • caching strategies
  • parallel tool calls
  • subagent patterns
  • Improve our observability and instrumentation
  • profile agent behavior
  • identify bottlenecks
  • drive optimization decisions
  • Stay current on new developments in agentic systems
  • bring those learnings back to the products we build
  • Passion for building effective domain-specific agents
  • Iterative mindset
  • develop proof of concepts
  • make decisions quickly
  • ship v0s
  • Comfortable with when and how to use evaluations to drive quality
  • Humble and adaptable about code and frameworks
  • drive adoption of new best practices
  • Proficiency in Python
  • experience working with LLM APIs and agent frameworks
  • Experience with shipping user-facing products

Other signals

  • building agentic systems
  • customer delight
  • task completion quality
  • shipping user-facing products