Legal AI Engineer (contractor)

Gusto Gusto · Fintech · Denver, CO +2 · Legal & Compliance

This role is for a Legal AI Engineer on a fixed-term contract to build foundational AI infrastructure for a legal team. The engineer will design, implement, and document AI systems and workflows, including a structured knowledge layer and AI-assisted processes for contract review and matter intake. The goal is to turn experiments into robust, shared systems that can be maintained internally after the engagement.

What you'd actually do

  1. Take the skills, workflows, and dashboards that individual team members have already built in Claude and package them into shared, maintainable assets the whole team can use.
  2. Stand up a structured, queryable knowledge layer fed by the team's existing research, positions, precedents, and playbooks — one that can be searched by any team member, can be invoked by automated workflows, and continuously ingests new information as the team works in the tool.
  3. Working from priorities set by legal ops and attorneys, implement AI-assisted workflows for the team's highest-volume use cases — likely including contract first-pass review, matter intake and routing, litigation operations to enable intake, routing and response drafting for subpoenas, demand letters and notices and prompt libraries for recurring legal tasks.
  4. Deliver a maintenance runbook for every system built and train designated team members on administration, so nothing requires the contractor to maintain it after the engagement ends.

Skills

Required

  • Claude or comparable LLMs
  • prompt engineering
  • agentic workflows
  • iterating on outputs until they're reliable
  • APIs
  • MCPs
  • integration experience
  • operating in ambiguity
  • translating business problems into working systems
  • working within internal technology governance processes
  • communicating with IT/AI teams on tool approvals, data access, and security reviews

Nice to have

  • Experience working alongside attorneys
  • understanding contracting workflows
  • matter intake
  • research cycles
  • how legal teams make decisions

What the JD emphasized

  • build foundational legal team AI infrastructure
  • design and stand up these systems
  • package them into shared, maintainable assets
  • implement AI-assisted workflows
  • Hands-on experience building and shipping AI-assisted workflows
  • actually standing systems up
  • Be ready to walk through something you built from prompt to production
  • core technical skill
  • build within the guardrails

Other signals

  • build foundational legal team AI infrastructure
  • design and stand up these systems
  • package them into shared, maintainable assets
  • implement AI-assisted workflows