Product Manager

Collins McNicholas Recruitment & HR Services Group; Oranmore; On-site; EUR 90,000 - 120,000; Full time

Job summary

Collins McNicholas Recruitment & HR Services Group is seeking a Product Manager to own the strategy, roadmap, and delivery for a healthcare domain used across the UK, Ireland and Australia. The role emphasizes AI-native execution and commercial accountability, with responsibility for go-to-market and customer outcomes.

You will lead cross-functional teams, articulate commercial value, and ensure alignment with regulatory requirements, delivering measurable revenue impact through strategic

Qualifications

• 5+ years as a Product Manager in a SaaS or platform environment.
• Experience defining requirements for AI-powered features and regulatory considerations in healthcare.
• Ability to translate product capability into commercial narratives for care organisations.

Responsibilities

• Own the vision, strategy, and roadmap for your domain, aligned with revenue priorities.
• Connect roadmap decisions to commercial outcomes (ARR, retention, expansion, win rate).
• Build the commercial case for major investments (pricing, packaging, revenue impact).
• Apply prioritisation frameworks to make defensible trade-offs.
• Contribute to sales enablement and enable product-driven strategic deals.
• Own go-to-market for major releases (positioning, launch plans, communications).
• Deliver against Voice of the Customer inputs and demonstrate impact on retention and satisfaction.

Skills

Commercial impact

ARR/NRR

AI-native practice

Stakeholder communication

AI tooling

Tools

Claude

Lovable

Jira

Confluence

Gong

Job description

The Product Manager will own the product strategy, roadmap, and delivery for a domain within our clients Group, used daily by care organisations across the UK, Ireland and Australia in a regulated healthcare environment.

Two things define how this role must be done.

First, you work AI-natively. You use AI tooling to do the heavy lifting of product work: research synthesis, analysis, drafting, and documentation. This is how you free your time for the work that matters most: customers, judgement, and decisions.

Second, you are accountable for commercial results. Your roadmap exists to win revenue, protect retention, and grow accounts. You will be expected to justify decisions in those terms and to show, after shipping, whether the outcome was achieved.

Responsibilities:

Product strategy and commercial ownership

• Own the vision, strategy, and roadmap for your domain, aligned with company-level strategy and revenue priorities.
• Connect every significant roadmap decision to a commercial outcome: new ARR, retention, expansion, win rate, or cost-to-serve. Articulate why something is, or is not, on the roadmap in terms a commercial audience respect.
• Build the commercial case for major investments: opportunity sizing, build versus buy, competitive positioning, pricing and packaging input, and expected revenue impact.
• Apply structured prioritisation frameworks (e.g. RICE, weighted scoring, opportunity-solution trees) to make transparent, defensible trade-offs.
• Contribute to sales enablement by translating product capability into commercial narratives that resonate with care organisation buyers, and support strategic deals where product depth matters.
• Deliver against priorities identified through the Voice of the Customer process and close the loop by evidencing their impact on retention and satisfaction back to customers and commercial teams.
• Own go-to-market for every significant release in your domain: positioning, launch planning, customer communications, and readiness across Sales, Customer Success, and Implementation.

AI-native ways of working

• Default to AI-first execution. You use tools such as Claude and AI analytics agents to compress research synthesis, analysis, PRD drafting, and documentation, and reinvest the time saved in high-value judgement work.
• Rapidly build and validate user journey prototypes with AI build tools (e.g. Lovable) before engineering effort is committed.
• Create and maintain your own reusable prompts, agents, and automations, and raise the bar for AI practice across the wider product team.
• Stay current with developments in applied AI for healthcare, including regulatory considerations (GDPR, NHS DTAC, CQC frameworks) and the ethical implications of AI in care settings.

Customer and market discovery

• Run continuous discovery: customer interviews, commercial conversations, usage analytics, support ticket analysis, and competitive research to surface unmet needs and validate opportunities.
• Define clear problem statements, opportunity assessments, and success metrics before committing engineering effort.
• Be the voice of the customer inside the product team. Engage directly with customers and prospects in discovery calls, design reviews, and feedback sessions.
• Work with Customer Success, Support, and Sales to convert churn signals, NPS feedback, ticket trends, and lost-deal insight into prioritisation inputs.

AI in the product

• Identify and evaluate where AI, machine learning, and large language models can be applied within the platform to automate workflows, surface predictions, or generate content.
• Partner with data and engineering teams to define AI feature requirements: training data needs, model evaluation criteria, responsible AI guardrails, and user-facing explainability.

Delivery and cross-functional leadership

• Write clear, well-structured requirements: user stories, acceptance criteria, and functional specifications engineering teams can build from without ambiguity.
• Partner with engineering leads on sprint planning, scope management, and technical trade-offs. Understand enough about the architecture to make informed decisions.
• Design for MVP and iterative delivery, balancing speed-to-learn with the quality thresholds a regulated healthcare context demands.
• Drive quality through the full lifecycle, from definition to post-launch measurement, and close the loop on whether shipped work delivered the commercial outcome predicted for it.
• Collaborate with Product Managers, Product Owners, Product Marketing, Engineering Managers, and Scrum Masters to align delivery across squads. Facilitate workshops and stakeholder sessions, bringing structure to ambiguous problems.

What You Will Bring

• Proven commercial impact. You can point to specific, measurable results you have driven in previous roles: revenue won or protected, churn reduced, pricing or packaging improved, or win rates lifted, and explain the product decisions behind them. Expect to discuss these with numbers at interview.
• Commercial fluency. Comfortable with ARR, NRR, churn, and deal economics. You can build a business case, defend a roadmap to a commercial audience, and connect product strategy to company outcomes rather than just managing a backlog.
• AI-native practice. Daily, hands-on use of AI tooling across the full product management workflow, not occasional experimentation. You can show how AI has changed the way you work, including prompts, agents, or automations you have built, and you bring a practical conceptual grounding in LLMs, embeddings, RAG, and prompt engineering.
• AI product experience. Experience defining requirements for AI-powered features, including evaluation criteria, bias considerations, user-facing explainability, and responsible AI principles in a regulated setting.
• Experience. 5+ years as a Product Manager in a SaaS or platform environment.
• Discovery and research strength. You have run interviews, surveys, and usability tests, and can synthesise findings into actionable insight. You practise structured prioritisation and outcome-based road mapping.
• Communication. Excellent written and verbal communication. You can write a clear PRD, present to executives, and facilitate a room of opinionated stakeholders.
• Regulated-domain comfort. Comfortable operating where compliance, data privacy, and clinical safety considerations shape product decisions.
• Tooling. Proficient with modern product tooling: Claude, Jira, Confluence, Lovable, and analytics platforms (Gong, Jiminny, HubSpot).
• Experience in healthcare, health-tech, or social care technology, with an understanding of CQC, HIQA, or equivalent regulatory frameworks.
• Familiarity with data modelling, or business intelligence tools; able to self-serve on data questions.
• Experience with platform or API product management, including developer experience and ecosystem thinking.
• Background in PE-backed or high-growth SaaS environments where speed, rigour, and commercial awareness are equally valued.