We are looking for a Product Manager to own delivery and product direction for the AI Acceleration team.
This is a hands-on role embedded within the engineering and data science team. You will own the roadmap, run Agile delivery, and act as the primary point of contact between the team and our internal teams, including practice groups, Firm leadership, Infrastructure, InfoSec, IT and our business development team.
Much of the work described below is already under way; what we need is someone to own and improve it, so our engineers can stay focused on building. As our team expands across the Firm, you will also be responsible for producing materials that explain our builds and how they operate, for internal audiences, client conversations and pitches.
We understand that you’re unlikely to arrive with a full knowledge of legal workflows or our stack. You will have the full support of the Senior Manager and the rest of the team as you settle into the role. Judgement, curiosity and an appetite for high levels of responsibility as we expand are all important qualities.
About the team:
We build bespoke AI solutions, drawing on software engineering and data science. We work at the boundary of enterprise-grade software, and we are regularly building services and applications nobody here has built before. That makes for a dynamic environment with real opportunity to learn and requires good judgement and critical thinking.
We are a tight-knit team that values ownership, honesty, and curiosity. We work across disciplines - engineering, data science, legal, and product - to deliver meaningful impact.
Our team is 100% remote and has a strong remote-first culture that enables everyone to feel like one team and contribute meaningfully to team decisions and activities.
Main Responsibilities:
Stakeholder management
- Act as the single point of contact between the AI Acceleration team and stakeholders, including partners, practice group heads, knowledge lawyers and central business services
- Gather, challenge and document requirements from non-technical users, and turn broad requests into clearly scoped work
- Manage competing expectations across practice groups, and set out trade-offs, timelines and constraints early
- Run regular showcases, steering updates and feedback sessions for stakeholders to demonstrate what is being built and why
- Build credibility with fee earners and learn their workflows in detail to aid productive discussions
- Agile delivery and project management
- Own end-to-end delivery for one or more Agile scrum teams, working closely with developers, UX engineers and data scientists
- Facilitate the full scrum cycle: backlog refinement, sprint planning, daily stand-ups, reviews and retrospectives
- Maintain the backlog in monday.com, with clear user stories, acceptance criteria and definitions of done
- Track velocity, throughput and delivery risk, escalate blockers and re-plan when circumstances change
- Coordinate releases, including UAT with pilot user groups, training material, rollout communications and post-launch support
Prioritisation and roadmap
- Own and maintain the product roadmap, balancing strategic firm priorities, fee-earner demand, technical debt and capacity
- Prioritise using WSJF, and be able to explain any sequencing decision to senior stakeholders
- Define success measures for each initiative, such as adoption and time saved, and report against them
- Decline or defer requests where necessary, so the roadmap is driven by priority
- Contribute to discussions on build versus buy options across the legal AI vendor market
Business development materials
- Own the library of client-facing and internal materials describing the team’s AI products, including capability statements, one-pagers, demo scripts, slide content and pitch inserts
- Partner with BD, marketing and pitch teams to respond to RFP technology sections, client innovation questionnaires and panel reviews
- Prepare and deliver product demonstrations to clients, prospects and internal audiences, adjusting depth for the audience
- Translate technical capability into commercial benefit without overstating it, since clients rely on these claims
- Maintain a repository of case studies, metrics and reference material, and keep it current as products change
Skills and Experience:
- Excellent written and verbal communication, with the ability to move between a technical stand-up and a partner briefing
- Ability to communicate effectively with stakeholders at all levels with the confidence to retain composure and hold a position when challenged
- Experience in a product, delivery, business analysis or engineering role
- Working knowledge of Agile and scrum. You do not need to have run every ceremony yourself, but you should understand backlog management in a tool such as monday.com, Jira or Azure DevOps and be able to run them purposefully, with minimal disruption
- Enough technical fluency to discuss architecture, APIs, data pipelines and testing with engineers. E.g. be able to fill in an audit form by inspecting a repo directly
- Genuine interest in AI and machine learning, and an understanding of the basics (large language models, prompt design, why models get things wrong) to build on quickly
- Comfortable working with incomplete information and shipping usable increments rather than waiting for complete specifications
- Bias towards simplicity and automation: when the same support query comes up twice, you update the service desk wiki instead of answering it again; when a progress update is due, you have AI draft it from the PRs that actually merged since the last one
Desirable Experience:
- A technical degree or hands-on background in software engineering or data
- Experience in a law firm, in-house legal function or legal technology vendor, and familiarity with legal workflows such as drafting, review, disclosure or matter management
- Exposure to legal AI tooling and the current vendor landscape
- Deep knowledge of retrieval-augmented generation, agentic workflows and their evaluation is welcome but can be developed in the role
- Experience contributing to bids, pitches or client-facing innovation conversations
- Awareness of professional and regulatory obligations relevant to AI use in legal services, including confidentiality, client data handling and emerging AI governance requirements
Additional Information
- Fully remote within the UK, with occasional travel to a Cleary London office for events
- Four-day working week, with no reduction in salary
- Salary of £70,000 to £90,000 per annum (dependent on experience)
If you meet some — not all — of the above criteria, we still encourage you to apply. We value learning ability, adaptability, and thoughtful engineering judgment above box-ticking.
If you are interested in applying, please submit a CV and short cover letter to the London Human Resources Team, LON-HR@cgsh.com.
Experience in product, delivery, business analysis or engineering; working knowledge of Agile and scrum; technical fluency to discuss architecture, APIs, data pipelines; interest in AI/ML; excellent communication; UK remote with occasional travel to London office.
Key Responsibilities
- managing stakeholders
- running agile delivery
- owning product roadmap
Skills & Tools
monday.com, Jira, Azure DevOps
Job Details
- Category: Product Management
- Seniority: Mid Level
- Commitment: Full Time
- Workplace: Remote — United Kingdom
- Salary: GBP 70,000 – 90,000 / year
- Languages: English
Benefits
- 4-day work week
About Cleary Gottlieb Steen & Hamilton LLP
A law firm with an AI acceleration team building bespoke AI solutions for legal workflows. — Industry: Consulting Services