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Job Description — Product Manager, Commercial & Technical (AI & Data Science)

Role summary

We’re hiring a hands‑on Product Manager who sits at the intersection of customer discovery , technical execution , and commercial strategy . This is a builder/operator (“product ninja”) role — not a pure strategy role. You’ll get your hands dirty: writing epics, shaping requirements, driving PRDs, partnering with engineering to translate into stories, and staying close to delivery realities.

You’ll be the glue across Sales, Clinical Ops, Engineering/R&D;, Finance, and Marketing , and you’ll help bring structure to ambiguity — especially when new opportunities land mid‑flight. You’ll also operate across multiple stakeholders, including other entities within the business and our parent company, to keep product direction aligned and execution predictable.

Reporting: Reports to an executive leader (BU leadership). Dotted line: Chief Operating Officer.
Seat: Leadership table within the AI & Data Science business unit.

Why this role exists

We’re scaling an AI & data science portfolio across Life Sciences, Public Health, and Primary Care . We need a product leader who can:

- Turn customer needs into crisp, testable requirements
- Balance delivery constraints with commercial urgency
- Drive productization (repeatable offerings) without losing near‑term deal velocity
- Own the commercial thesis : positioning, packaging, pricing, and competitive differentiation
- Improve how we intake and evaluate “big opportunity” requests, so we don’t thrash

Key responsibilities

1) Product vision, strategy, and roadmap (BU-level)

- Own product strategy and roadmap for one or more product lines (e.g., patient identification workflows, smart summary/narrative, smart search, evidence generation, data services).
- Build a roadmap that is:
- grounded in customer value,
- feasible with engineering capacity,
- actionable for Sales and Delivery.

- Define outcomes and success metrics (adoption, cycle time, quality, customer impact).

2) Customer discovery + feedback loops (field + delivery + users)

- Run structured discovery across:
- Sales pursuits (pre‑sale requirements, objections, win/loss),
- Clinical Ops delivery learnings (what breaks at implementation),
- End‑user feedback (clinicians, analysts, research teams).

- Convert insights into clear choices:



what’s productized vs bespoke, what’s in/out of scope, and what we deprecate.

3) Hands‑on execution: epics, PRDs, and “engineering‑ready” clarity

- Write and maintain PRDs , epics, acceptance criteria, and edge cases.
- Work directly with engineering/R&D; to translate epics into implementable stories and ensure requirements are unambiguous.
- Drive a high bar for product artifacts (PRDs, specs, release notes, enablement docs) to reduce churn and rework.
- Partner on release planning and ensure delivery impact is understood early (dependencies, data readiness, operational workflow changes).

4) UI/UX and user workflow design (practical, not theoretical)

- Bring a solid intuition for workflow + UI/UX : help shape user journeys, reduce friction, and ensure product experiences are intuitive.
- Partner with design/engineering to validate concepts quickly (wireframes, prototypes, usability feedback) and iterate.

5) Commercial strategy ownership (pricing, packaging, competitive)

- Own product packaging and pricing strategy (with Sales/Finance input): value metrics, pricing fences, commercial guardrails.
- Maintain competitive intelligence and differentiation narratives.
- Ensure “deal‑to‑product” alignment: what we sell can be delivered and scaled.

6) Launches, messaging, and go‑to‑market enablement (with Marketing + Sales)

- Partner with Marketing and Sales to craft:
- product messaging and positioning,
- launch plans,
- webinars/demos,
- customer‑ready materials (decks, one‑pagers, FAQs, talk tracks).

- Act as the “single throat to choke” for making sure launches are coordinated and the field is enabled.

7) Cross‑functional prioritization + opportunity intake (no thrash)

- Drive prioritization across Sales, Clinical Ops, Engineering, Finance — make tradeoffs explicit.
- Establish a repeatable intake model for “big opportunities”:
- problem statement → business case → feasibility/sizing → resourcing tradeoffs → decision gates





- Keep stakeholders aligned across internal entities and the parent company when priorities intersect.

8) AI‑augmented product management (high velocity)

- Use AI tools to accelerate discovery synthesis, requirement drafting, competitive research, and enablement creation.
- Build lightweight systems/templates that compound throughput.

What success looks like (first 90 days)

- A clear portfolio map and narrative: what we sell, to whom, and why we win .
- One prioritized roadmap with explicit tradeoffs tied to capacity.
- A repeatable opportunity intake/gating process (so we handle the next “patient registry‑like” request cleanly).
- PRDs + epics for priority initiatives that engineering can execute with minimal ambiguity.
- A v1 packaging/pricing hypothesis for the top offerings with proof points and differentiation.
- At least one coordinated launch/enablement motion (e.g., webinar + collateral + talk tracks) executed end‑to‑end.

Required qualifications

- 7+ years product management (or equivalent end‑to‑end product ownership).
- Strong technical fluency: able to engage credibly with engineering/R&D; and reason about data pipelines, integrations, constraints, and tradeoffs.
- Demonstrated ability to write PRDs/epics and drive execution through engineering delivery.
- Strong commercial acumen: packaging/pricing instincts and customer‑facing confidence.
- Excellent written communication: crisp PRDs, decision memos, and field‑ready enablement content.

Strongly preferred (healthcare + regulated AI)

- Healthcare domain experience, ideally with EMRs/EHRs , clinical workflows, and healthcare data interoperability.
- Experience launching or operating AI/ML products in highly regulated / privacy‑sensitive environments (health data, security constraints, compliance‑driven change control).
- Comfort with privacy/security norms and regulated operating expectations (e.g., PHIPA/HIPAA‑like environments).

Working style / operating principles

- Hands‑on operator: happy to roll up sleeves, write, iterate, and unblock teams.
- High ownership + high velocity with a bias for clarity.
- Comfortable in ambiguity; creates structure and decision gates.
- Collaborative and direct; can drive decisions across multiple stakeholders and entities.

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Apply on Kit Job: kitjob.ca/job/2fsexv

📌 Product Manager (Toronto)
🏢 HEALWELL AI
📍 Toronto