Senior Product Manager

We are hiring a Senior Product Manager to own a core product surface on our platform. This spans diagnostics, intake, scheduling, status updates, and communications across web, mobile, messaging, WhatsApp, SMS, chatbot, and voice channels, together with the hand-offs into the operational workflows behind them. You will sit in the Product team and report to the Head of Product. You will work closely with design, engineering, data, operations, customer teams, and AI specialists to build product experiences that are simple, reliable, and practical to operate. This is an AI-native product role. We expect you to use agentic prototyping and spec-driven product development as part of your normal workflow, and to judge which models fit a given problem: when a hosted commercial model is the right call, and when privacy, GDPR, or data-residency constraints mean an open-source model in our own cloud environment is better. You do not need to build these systems yourself, but you do need the technical understanding to navigate the trade-offs and direct the work. You will turn user problems into clear specs, define quality gates for AI-powered experiences, and decide when automation is ready for production.

Product Strategy, Discovery, and Delivery

• Identify and model the jobs-to-be-done and workflows for users, providers, and operational teams, weighing operational constraints and commercial outcomes, and capture them as clear specs that engineering and design can act on.
• Prioritise work using product analytics, operational data, support contact drivers, customer commitments, and AI-readiness risk.
• Own the roadmap for the product suite, spanning diagnostics, scheduling, communications, chatbot, voice-agent, and self-service surfaces.
• Lead discovery with users, housing providers, customer teams, operations, and internal users.
• Translate ambiguous service problems into sequenced bets, measurable outcomes, and crisp trade-offs for senior stakeholders.
• Own go-to-market for customer-facing launches: launch readiness, release sequencing, enablement, and internal and external launch communications with product marketing, customer, and operations teams.
• Align product, engineering, design, data, operations, customer success, implementation, and support teams around scope, launch readiness, and adoption.
• Improve user journeys that cross multiple operational systems, including issue classification, contractor availability, scheduling changes, notifications, and case escalation.
• Measure product outcomes through experiments, cohort analysis, operational metrics, qualitative research, and post-launch reviews.

AI-Native Product Development

• Use agentic prototyping tools to test interaction patterns, conversation flows, scheduling logic, and multimodal diagnostics before committing engineering capacity, deciding whether a problem calls for straightforward automation, a copilot feature, a fully agentic workflow, or a mixture.
• Define specifications, acceptance criteria, and launch criteria for AI-powered product experiences.
• Build and own evals for these experiences: define what good output looks like, assemble eval sets that check outputs against the required format and quality, and use the results to improve the solution.
• Partner with engineering and AI specialists on LLM orchestration, tool calling, RAG, context management, prompt iteration, model selection, and cost-performance trade-offs.
• Design human-in-the-loop controls for cases where AI confidence, safety risk, or operational complexity requires escalation.
• Establish quality metrics for chatbots and voice agents, including task completion, containment, hand-off success, latency, retrieval precision, and hallucination rate, and account for how voice agents integrate with telephony and contact-centre tooling.
• Define the privacy, consent, auditability, and data-handling requirements for customer-facing AI features, especially where personal or sensitive data is involved.
• Work with Security, Legal, Privacy, and customer stakeholders to agree guardrails for automated decisions, user communications, and autonomous workflows.

We offer:

• A competitive compensation package
• 25 days annual holiday, plus one additional day for every year served, up to a maximum of 5 additional days
• Flexible working environment, including the option to work abroad
• Private healthcare for you and your immediate family, with discounted gym membership and access to optical, dental, and private GP services
• Enhanced parental leave
• Life insurance at 4× salary
• Employee assistance programme
• Company volunteering day and charity salary‑sacrifice scheme
• Learning management system powered by Udemy
• Referral bonus and charity donation when someone you introduce joins the company
• Season ticket loan, Cycle to Work, electric vehicle, and Techscheme programmes
• Pension scheme
• Company-sponsored lunches, dinners, and social gatherings
• Fully stocked kitchen with drinks, snacks, fruit, and breakfast cereals

Experience and Qualifications

• Product management experience in B2B SaaS, marketplace, workflow, healthtech, proptech, fintech, or another regulated or operational domain.
• Demonstrable experience building native mobile app products, including ownership of a native iOS or Android app from discovery through release and ongoing iteration.
• Demonstrable experience shipping AI-powered product features from prototype to production, including controlled rollout and post‑launch iteration, ideally across conversational AI, voice agents and telephony, workflow automation, decision support, diagnostics, or intelligent self‑service.
• Strong working knowledge of multimodal models, LLM capabilities and limitations, prompt engineering, tool calling, embeddings, RAG, and AI observability.
• Fluency with evals: defining what good output looks like, building eval sets to check that outputs meet the required format and quality, and using the results to improve the solution.
• Hands‑on fluency with agentic prototyping and AI‑assisted product development tools, such as agentic IDEs and prompt‑driven prototyping environments, used to produce testable prototypes.
• Working knowledge of low‑code automation platforms such as n8n, Tray.io, Workato, or Zapier, enough to prototype workflows, scope feasibility, and direct engineering, without owning production builds yourself.
• Sound understanding of AI risk in production, including hallucination, retrieval failure, automation bias, latency, cost, drift, privacy, and human escalation.
• Excellent written and verbal communication across technical, non‑technical, and senior stakeholders.
• High ambition and a strong bias for action, with the drive to deliver a large roadmap at pace and a positive, can‑do attitude.

6+ years of product management experience, including ownership of customer‑facing product surfaces from discovery through launch and iteration. Experience working closely with engineering, design, data, operations, customer success, and senior stakeholders. Experience with products that involve scheduling, logistics, case management, customer support, field operations, regulated workflows, or high‑volume service journeys. Located in London and able to work from our London office on a hybrid basis. Right to work in the United Kingdom.