Technical Product Manager

About forsyte

forsyte builds an AI powered risk assessment and compliance platform for law firms, helping them meet their anti-money laundering, client due diligence, regulatory and practice specific risk obligations. Our multi agent platform guides fee earners and compliance teams through client and matter risk, from identity and source of funds to PEPs, sanctions, file reviews and a complete risk register. We believe in human centric AI: our technology supports practitioners' professional judgement rather than replacing it.

Our vision is one risk wrapper for every law firm, delivering enterprise technology that seamlessly supercharges their existing tech stack. We are a fast-growing ambitious UK legal technology company, working remotely as one team.

About the role

forsyte has no product owners. Our Product Engineering team designs and builds the product, and you will work directly with our CPO, and engineering team to translate the forsyte vision and mission into products that revolutionise how law firms mitigate risk. You will be hands on: building prototypes, shaping how our AI agents behave and working side by side with our engineers from first idea to go live.

The CPO collaborates with our Exec team to set the product strategy and roadmap. You will give them the evidence and insight to make the right prioritisation calls, showing what matters most to deliver against our company OKRs and client expectations, and what each choice costs us in opportunity.

What you'll do: AI product discovery and build

• Build working prototypes yourself using AI tools, so ideas can be tested with clients and engineers before they enter the build.
• Collaborate closely with our product engineers from problem framing through to go live, working alongside them rather than handing over requirements.
• Shape how our AI agents behave: help write and refine agent instructions, agree what the app decides and what the agent owns, and define the outputs practitioners see.
• Contribute to our RAG pipelines and agentic workflows, including the sources our AI draws on, how answers are cited and how agents hand work to one another.
• Define how we test AI features, including test cases, accuracy measures and the checks each agent version must pass before release.
• Keep the practitioner in control, designing for explainability, citations and professional judgement in line with our human centric AI principles.
• Make sure requirements cover data protection, security and regulatory needs from the start.

What you'll do: prioritisation and insight

• Support the CPO’s prioritisation decisions with a clear view of what matters most to deliver against our company OKRs and client expectations.
• Set out the opportunity cost of each choice, weighing commercial value, client need, development effort and ongoing support.
• Review requests with clients, Commercial and Customer Success to establish the problem, who it affects and the evidence behind it.
• Assess options with engineers, including whether an existing feature or agent could meet the need.
• Challenge requests where the benefit does not justify the complexity or cost, or where they pull us away from our vision.
• Write clear problem statements and acceptance criteria so engineers know what good looks like.

What you'll do: go lives, betas and early adopters

• Lead product go lives, so new releases reach clients at the earliest opportunity.
• Run beta projects and early adopter groups: recruit the right firms, set clear goals and capture what we learn.
• Agree what success looks like for each release, then measure adoption and client outcomes and feed the findings back to the CPO and engineers.
• Work with Customer Success so clients are supported through go live, and with engineering to prioritise any fixes.

What you'll do: adoption, analytics and reporting

• Own our Pendo journey, including in-app guides, onboarding journeys and product analytics.
• Turn usage data into insight on what clients value, where they struggle and where adoption needs support.
• Analyse usage, client and delivery data, and report clearly to the CPO and leadership team on adoption, client outcomes and progress against our OKRs.
• Build reporting that teams can rely on, so decisions are based on evidence rather than anecdote.
• Keep our use of analytics within our agreed data protection approach.

What you'll do: integrations and vendors

• Manage the integration roadmap, working with engineers, clients and partners to understand where forsyte connects into each firm's tech stack.
• Understand how information moves between forsyte and systems such as case management, document management, and identity and screening providers, well enough to scope client needs and explain them clearly.
• Track integration commitments and dependencies, and flag risks to delivery early.
• Manage our relationships with product vendors and technology partners, including identity, screening and analytics providers: track performance and service levels, stay close to their roadmaps and raise issues early.
• Support vendor reviews and renewals with clear evidence on value, cost and risk.

What you'll do: commercial product proficiency

• Build the Commercial team's product proficiency through training, demo support and clear explanations of our AI and integrations.
• Make sure Commercial understands what the product does today and the agreed path ahead, so nothing is promised that has not been agreed.
• Bring prospect and market insight back into product decisions.

What you'll do: domain and market

• Apply a deep understanding of how law firms manage AML risk and compliance, so our product reflects their workflows, obligations and constraints.
• Keep up to date with regulation, sector guidance, the legal tech market and competitors, and share insight across the business.

How you'll work:

Our values shape how we expect you to approach the role.

Rethinking. You question how things are done and find simpler, smarter ways to manage recurring work, meetings and communication.

Curiosity. You explore new tools and processes, learn how each team works, and get to know the CPO's working style well enough to anticipate what they need before they ask.

Accountability. You own actions through to completion, follow up without being chased, and build strong working relationships across the business and with clients.

What success looks like:

After 6 months

• Prototypes you have built have been tested with clients and have shaped what our engineers build.
• The CPO receives clear, evidence based recommendations on priorities and opportunity cost.
• At least one beta or early adopter group has taken a release through to go live.
• Pendo journeys and analytics are in place for our core workflows.

After 12 months

• New releases routinely reach clients through early adopters at the earliest value point.
• Every AI feature ships with agreed test cases and success measures, and adoption is tracked after release.
• The Commercial team demonstrates and explains the product confidently, including our AI and integrations.
• The integration roadmap is clear, tracked and understood across the business.
• Vendor relationships are well managed, with performance tracked and renewals planned ahead.
• Regular product reporting is trusted and used by the CPO and leadership team.

How your performance is measured:

Your performance is measured against OKRs agreed with the CPO. Your objectives link directly to the shared OKRs of Product Engineering, Commercial and Customer Success, and to forsyte's revenue goals, so your success is tied to the success of the wider team.

Key results will typically cover:

• Revenue: the contribution of new features, modules and integrations to new business, upsell and cross sell.
• Adoption: take up and active use of new releases, tracked through Pendo and product analytics.
• Speed to client: the time from a feature being built to it being in the hands of clients through betas, early adopters and go lives.
• Quality: AI features meeting agreed accuracy measures, with fewer issues after release.
• Team outcomes: progress against shared OKRs, including Commercial confidence with the product and client satisfaction.

Progress is reviewed regularly with the CPO, and OKRs are refreshed as company priorities change.

What you'll bring:

Essential

• Senior product management experience on technical software products, ideally in a fast paced SaaS start up or scale up.
• Proven experience working on AI or LLM products in production.
• Hands on experience building prototypes with AI tools.
• A practical understanding of RAG, agentic workflows, prompting and how to test AI outputs.
• Comfortable reviewing agent outputs, JSON and logs alongside engineers, without needing to be a production engineer.
• Experience running betas, pilots or early adopter programmes and taking products to go live.
• Experience using product analytics to drive adoption.
• Strong data analysis and reporting skills, turning usage, client and commercial data into clear insight and recommendations.
• Experience managing relationships with vendors and technology partners.
• Sound, evidence-based judgement on prioritisation, with the confidence to challenge and explain why.
• Excellent written and verbal communication, able to explain technical choices in plain English.

Desirable

• Domain knowledge of AML and client due diligence in law firms, including the Money Laundering Regulations 2017, LSAG guidance, SRA expectations, source of funds and wealth, PEPs and sanctions, and the role of the MLRO and MLCO.
• Experience coaching or mentoring others, and an interest in helping build a team as forsyte grows.
• Experience optimising Pendo or a similar product analytics and in-app guidance platform.
• Experience of integrations with legal case and practice management systems.
• Experience training sales or commercial teams on product.