Engineering Manager (Remote in Canada)

Intrahealth

2d•Remote

About The Position

Intrahealth, a subsidiary of HEALWELL AI Inc. (TSX: AIDX), is an enterprise class EMR provider supporting approximately 20,000 providers and the care delivery of tens of millions of patients and clients across Canada, Australia and New Zealand. Intrahealth provides a suite of flexible software solutions to a wide variety of customers including health authorities, public health, community health, home care, and primary care professionals. Intrahealth's solution is highly configurable and is ideal for complex health environments. To learn more about Intrahealth, please visit https://intrahealth.com. Intrahealth is seeking an Engineering Manager to lead multiple AI-first software development pods building our new electronic medical record platform. This is a greenfield opportunity focused on shaping a new product and engineering organization from the ground up through AI-first delivery practices. You will lead a team of engineers working across 3–5 pods and partner closely with Product, Design, and Architecture. You will establish team structure, technical direction, AI-first delivery practices, and quality expectations, while ensuring consistent throughput and maintaining correctness, security, and regulatory-minded engineering practices expected in healthcare software. Our ideal candidate has deep industry experience, strong product engineering instincts, and a proven ability to lead teams through ambiguity. AI fluency is essential. You track where the industry is going in AI-assisted and agentic software development, and you can operationalize it into reliable, repeatable delivery in a greenfield environment.

Requirements

7+ years of industry experience building production software, including experience leading teams or leading major initiatives end-to-end.
Demonstrated experience managing engineers across multiple teams, pods, or workstreams in a product engineering environment.
Demonstrated hands-on fluency with AI-assisted development tools and agentic workflows; AI fluency is a must-have and the most important skill for this role.
Proven ability to operationalize AI-first development into reliable delivery systems, practices, and guardrails rather than ad-hoc usage.
Proven ability to lead greenfield or early-stage product development through ambiguity and change.
Strong technical judgment and fluency in modern software engineering practices, including architecture, APIs, data modeling, CI/CD, performance, reliability, and testing.
Strong React and .NET engineering background, with the ability to guide technical direction credibly across the stack.
Strong problem-solving and analytical skills, and the ability to debug complex system and organizational delivery issues, including failures in AI-assisted workflows.
Excellent communication skills and stakeholder management; ability to set expectations and deliver predictably.

Nice To Haves

Experience building healthcare / EMR software or other regulated systems.
Experience leading teams through platform or product formation, including defining ownership, engineering practices, and delivery models from scratch.

Responsibilities

Own outcomes for the team: delivery, quality, operability, and predictability. Manage commitments, scope, and trade-offs with stakeholders.
Lead AI-first engineering execution across pods:
Define and evolve how work is structured across multiple pods, including ownership boundaries, dependencies, and delivery coordination.
Establish and scale AI-first development practices across pods, including how engineers use AI tools, agentic workflows, code generation, verification loops, and review discipline.
Create clear ways of working that support autonomy within pods while maintaining alignment across the broader platform.
Greenfield AI-first delivery leadership:
Help shape and build the engineering organization, systems, and practices required to deliver a new EMR platform from the ground up.
Drive clarity in ambiguous problem spaces, turning product and technical goals into actionable, testable increments using AI-first development approaches.
Ensure the team builds systems that maximize engineering leverage through AI, automation, and strong delivery workflows.
Technical leadership:
Guide system architecture and engineering practices across the new platform, including frontend, backend, APIs, and shared services.
Ensure the new system is scalable, secure, accessible, and maintainable.
Partner with senior engineers and architects to make sound technical decisions and manage cross-pod technical risk.
Provide technical leadership on where and how AI-assisted and agentic development should be applied, and where guardrails are required.
Quality and risk management:
Implement CI/CD quality gates (unit/integration/e2e), regression protection, static analysis, dependency controls, and release checks.
Define and enforce security/privacy-minded practices appropriate for healthcare data.
Establish guardrails and validation practices so AI-assisted development remains correct, maintainable, and auditable.
People leadership:
Coach engineers and technical leads in AI-first development practices and create a healthy, accountable engineering culture grounded in strong engineering habits (testing, design, PR discipline, operational ownership).
Support career growth, performance management, and team development across a growing organization.
Build a learning culture that helps the team keep pace with rapidly evolving AI tooling without destabilizing delivery.
Cross-functional execution:
Partner with Product to shape work into well-specified, testable increments.
Communicate clearly to technical and non-technical stakeholders, escalating risks early with concrete mitigation.