Build AI agent systems for legal workflows, optimizing performance via prompt engineering, model selection, tools, and evals. Requires 3+ years experience, Python proficiency, and LLM/agent framework expertise for mid/senior/staff levels.
165k – 312k
On-siteML Engineering
About the role
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.
3+ 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.
Lead architectural design and implementation of production-grade multi-agent frameworks, LLM orchestration, and autonomous AI agent systems from the ground up at Mozilla's New Products incubator. Requires 7+ years software engineering experience including 2+ years building agentic systems, startup mentality, and deep proficiency with AI tooling.
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