HEALWELL AI (TSX: AIDX)
Product Manager
HEALWELL AI (TSX: AIDX)Canada6 hours ago
Full-timeOther
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

  • 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)
  • 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
  • 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)
  • UI/UX and user workflow design (practical, not theoretical)
  • Bring a strong 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
  • 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
  • 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
  • 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
  • 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

Key Skills

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