Technical Product Manager

THE ROLE

We need a Technical PM who has been in the trenches as a software engineer and knows what it really takes to ship production software. You will own end-to-end product delivery across one or more core product areas — from discovery and roadmap through to launch and iteration. You will work daily with engineering, design, data science, and clinical stackholders to build product that is loved by users and respected by regulators.

WHAT YOU WILL DO

Product Roadmap
Own the product roadmap end-to-end — define the Epics, sequence features by impact vs. effort, and communicate trade-offs clearly to engineering, design, and business stakeholders.
Translate business goals and user problems into a prioritised backlog; use frameworks like RICE, opportunity scoring, or jobs-to-be-done to make sequencing decisions defensible, not just intuitive.
Drive quarterly planning cycles — align product bets with revenue goals, capacity constraints, and platform health; flag conflicts early.
Technical Execution & Engineering Partnership
Write technically precise PRDs that include API contracts, data models, state machines, edge cases, and explicit error-handling expectations — not just user stories.
Participate actively in architecture and system design discussions; understand and articulate trade-offs between monolith vs. microservices, sync vs. async patterns, and build vs. buy decisions.
Review technical specs and ERDs for completeness; spot scope creep, hidden dependencies, and under-specified integrations before sprint kick-off.
Own the technical debt roadmap alongside engineering — balance new feature velocity with platform health, scalability, and security hygiene.
Understand SaaS infrastructure fundamentals: multi-tenancy, role-based access control (RBAC), SSO/SAML, rate limiting, webhooks, and API versioning. Able to make product decisions that affect these layers intelligently.
Run sprint ceremonies (planning, grooming, retros) and maintain the engineering team's flow — unblock dependencies, resolve ambiguity, and shield the team from context-switching.
Data, Metrics & Analytics
Define success metrics for every feature before it ships — activation rates, feature adoption, time-to-value, retention impact. Run post-launch reviews against these benchmarks without being asked.
Instrument product analytics from the requirements phase — specify event schemas, funnel definitions, and cohort logic for the data/engineering team.
Integrations, Platform & Ecosystem
Own the product's integration strategy — third-party APIs, webhooks, SDK/embed scenarios
Collaborate with the security and compliance team on features that touch PHI/PII — define data residency requirements, consent flows, audit logging, and access control at the product spec level.
Go-to-Market & Stakeholder Management
Partner with sales and customer success on feature positioning, release notes, and customer-facing documentation; translate engineering outputs into clear business value.
Manage stakeholder expectations across product, engineering, sales, and clinical SMEs — escalate risks early, communicate scope changes in writing, and keep every stakeholder in the right information loop.
Contribute to pricing and packaging decisions for new features — understand SaaS monetisation levers (seat-based, usage-based, module tiers) and their product implications.

MUST-HAVE QUALIFICATIONS

Experience
4–5 years of product management experience on a B2B SaaS product, owning roadmap and delivery end-to-end with full accountability for outcomes.
2–3 years of prior software engineering experience in a production environment (any stack — backend, frontend, or full-stack). You have shipped code, managed deployments, and debugged production incidents.
Demonstrated track record of launching SaaS features that drove measurable improvement in activation, retention, or revenue — with numbers to back it up.

Technical Skills

Comfortable reviewing REST API specs (OpenAPI/Swagger), understanding authentication patterns (OAuth 2.0, JWT, API keys), and writing acceptance criteria that include API behaviour.
Able to read a system architecture diagram, understand data flow between services, and ask the right questions about scalability, latency, and failure modes.
Working knowledge of SaaS infrastructure concepts: multi-tenancy, RBAC, SSO/SAML, CI/CD pipelines, feature flags, and deployment environments (staging vs. production).
Hands-on with product analytics tools — Mixpanel, Amplitude, Heap, or equivalent — including defining event taxonomies, not just reading dashboards.
Product Skills
Writes PRDs that include functional specs, non-functional requirements, data requirements, and explicit out-of-scope boundaries — no ambiguity handed off to engineering.
Practised in agile delivery: sprint planning, backlog grooming, sprint reviews, and retrospectives. Comfortable in Jira, Linear, or equivalent; knows how to write a ticket that doesn't require a meeting to explain.
Experience defining and tracking OKRs or product KPIs at the feature and product-area level; can connect daily work to business outcomes.
Can conduct user interviews, synthesise qualitative feedback, and convert it into prioritised problem statements — not just a feature wish list.
Soft Skills & Mindset
Excellent written communication — can distil a complex technical problem into a one-page brief that a non-technical exec can act on and an engineer can build from.
Strong cross-functional influencer — comfortable pushing back on engineering scope creep, design gold-plating, and sales feature requests with data and user evidence, not authority.
High ownership mindset — you treat the product like it is yours, escalate blockers fast, and don't wait to be told what to do next.

NICE-TO-HAVE QUALIFICATIONS

Experience in health-tech, clinical AI, or regulated software environments (SaMD, HIPAA, HL7/FHIR).
Familiarity with AI/ML product development — understanding of model evaluation, data pipelines, or MLOps workflows.
Prior exposure to B2B enterprise sales cycles and hospital/clinic procurement dynamics.
Background in neuroscience, clinical psychology, or adjacent fields.
Experience with design tools (Figma) and ability to contribute to wireframe-level discussions.