About the role
You will help in-house legal teams and law firms move from point solutions to an agentic way of working. That means advising clients on where AI agents can run or support legal work, then designing, configuring and governing those agents on an Agentic OS – a platform that orchestrates multiple AI agents across workflows, systems and functions.
The role
suits a consultant who combines legal-domain depth with hands-on technology delivery, and who can facilitate decisions between General Counsel, legal operations, IT and risk teams.
Key responsibilities
- Agentic OS consulting and implementation Assess and advise: map current legal processes, identify agent use cases, and prioritise them by value, risk and feasibility.
- Design the agentic operating model: define which tasks agents perform, where human-in-the-loop review sits, and how work is escalated and approved.
- Implement: configure agents, orchestration flows, prompts and playbooks, knowledge sources and integrations with other platforms.
- Scale: run pilots, define success metrics (cycle time, cost, accuracy, adoption), and lead change management and training through to rollout.
- Domain delivery Contracts: agent-led intake, first-pass review against playbooks, negotiation support, obligation and renewal tracking.
- Compliance: regulatory change monitoring, obligation-to-control mapping, policy workflows and third-party due diligence.
- Litigation and matter management: matter intake and triage, legal spend and e-billing, outside counsel management and reporting.
- Consulting and leadership Lead client workshops, current-state assessments, business cases and implementation roadmaps.
- Own workstreams, guide junior team members, and contribute to proposals, demos and pre-sales.
- Required qualifications 5+ years' experience, ideally with a Big Four or consulting firm, an ALSP, a legal tech vendor's professional services team, or an in-house legal operations function.
- Hands-on experience delivering GenAI or agentic AI solutions: workflow and agent design, prompt and playbook design, and evaluation of AI output.
- Ability to translate legal requirements into technical design, and explain AI capabilities and risks to lawyers in plain terms.
- Strong stakeholder management and facilitation skills with GCs, legal operations leaders, CIOs and risk teams.
Education:
law degree (LLB, BA LLB, LLM) or a degree in engineering, computer science or information systems. Candidates should be strong in one and fluent in the other.
