What You’ll Work On

Discovery and customer work:

• Run structured customer interviews with compliance officers, due diligence researchers, and risk teams to understand what works, what does not, and what should exist next.

• Translate findings into clear opportunities, tested assumptions, and well framed problems for the team to work on.

• Bring evidence rather than opinion to roadmap and prioritisation discussions.

Delivery and craft:

• Own the product backlog: write user stories with acceptance criteria that engineers can build from.

• Run sprint planning, refinement, and review for your product area, in close collaboration with engineering and design.

• Ship release notes, and internal change communications that keep commercial, support, and operations in the loop.

Workflow and integrations:

• Work on workflow heavy features for specialist users (compliance researchers, analysts, reviewers), where the product earns its place by removing friction from real work

• Specify API integrations between our platform and third-party systems, with clear contracts and a sharp eye for edge cases

• Balance speed with the reliability and auditability demands of a regulated domain.

AI augmented product work:

• Work on features where AI is in the loop: knowledge graph queries, document analysis, vendor screening, risk evaluation.

• Use AI tools actively in your own workflow: research synthesis, story drafting, competitive analysis, data shaping.

• Be willing to get your hands dirty with AI tools across the whole product workflow: prototyping flows, mocking up designs, even shipping rough features for internal testing. We want someone who treats their own way of working as a product to optimise.

What We’re Looking For

Must have:

• Proven product management experience, ideally in B2B SaaS or workflow heavy software.

• Solid craft on the fundamentals: backlog management, user story writing, acceptance criteria, release notes, sprint hygiene.

• Genuine experience running customer discovery: you have sat in front of users, asked the right questions, and let findings change your mind.

• Comfort with data: you can read and interrogate product metrics.

• Ability to work across technical and non-technical stakeholders without losing the thread of either.

Strong advantage:

• Hands on experience shipping AI assisted product features (LLMs, agents, retrieval, evals, prompt or context engineering).

• Experience in risk, compliance, KYC, AML, financial crime, due diligence, or another similar regulated domain.

• Familiarity with knowledge graphs, search, or knowledge management systems.

• Experience working in a start-up or early-stage environment, with comfort in the ambiguity, pace, and shifting priorities that come with it.

How We Work

These are not aspirational values on a wall; they are how we operate day to day:

• Discovery is a habit, not a phase. We want to be in front of customers every week, not every quarter.

• Outcomes over outputs. Shipping a feature is not the point. Changing a behaviour or moving a metric is.

• Small bets, tight loops. We prefer well measured experiments to long roadmaps.

• AI tooling raises the floor, not lowers the bar. We use it to move faster on the right things, not to skip the thinking.

• An open, low ego culture. We move forward by sharing ideas and challenging each other honestly. You will feel at home if you raise issues early, push back when you disagree, and change your mind when the evidence asks you to.