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Added 7 mins ago
Supervisor, Health Information Management
Alberta Health Services
Fort McMurray, AB
Temporary
…in Health Information Management and reports directly to the Manager, Health Information Management. This position is responsible and accountable for providing the direction, team…
Added 7 mins ago
Unit Supplies Coordinator - Patient Care Supply
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Full-time
Under the direction of the Manager, Health Services Supply:
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General Duty Nurse (N2) - Women's Health Labour & Delivery
Shared Health-Soins Communs
Winnipeg, MB
Full-time
Under the general supervision of the Manager Health Services, the Registered Nurse (RN) is responsible for providing professional registered nursing services for patients, including those…
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Data Engineering, Cloud Migration & Platforms Engineer
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The University of British Columbia
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Communicates with customers as required to ensure the efficient delivery of service.
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Partner Success Manager
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Groom & Associés / Associates

Software Engineering Manager - VP level

Greater Montreal Metropolitan Area, QC, Canada

Pay: $190,000 to $200,000 CAD / year
Job type: Full-time
Apply by: Oct 28, 2026
Posting language: English
Posted: Sep 28, 2026

Apply About employer

Applications open in a new tab.

Original job description

Manager of Engineering

Full Time | Montréal, QC, CA (Hybrid) |Development / Engineering | Reports to: CTO

Salary range: CAD $190,000-200,000+ annually,

Bonus: 15% target if all objectives are met with a mix of personal/team and company

objectives. (i.e., a portion of the 15% is dependent on the company hitting its targets - mix is

TBD right now. Could be 50/50 or could be higher on company for VPs - that is the discussion

right now.)

Equity: Yes for this position. Amount TBD with the right candidate.

About the company

We are a SaaS company with a live research data management and analysis platform that brings together multi-modal data - including imaging, genetics, behavioral, and biosample data - for large-scale research studies. Thousands of researchers worldwide rely on our platform to accelerate scientific discovery.

Our diverse team includes experts in medicine, engineering, software development, imaging, epidemiology, and genetics. We foster innovation, collaboration, and continuous learning while empowering scientists to focus on research instead of technology.

About the Role

The team is hiring a Manager of Engineering to lead the engineering group that builds and operates our research data management platform. Reporting to the CTO, you will lead how the platform is designed, built and delivered, and you will be the senior technical authority for the engineering group day to day.

This is a broad, high-ownership role. You will contribute at the level of architecture and direction as well as run delivery. You will stay technical enough to hold the respect of strong developers and to step into hard problems yourself, while working to ensure the health and scalability of the platform.

AI is not optional at our company: we expect every leader on this team to have already internalized AI and to model that for the organization. So the person we’re looking for will bring demonstrated, hands-on fluency with AI: both in how they work (AI-assisted development, tooling, code review) and in what they build (integrating AI capabilities into the platform.)

Set the standard for AI-native engineering practice across the development team: agentic workflows, LLM-assisted development and review, copilot tooling and AI-powered engineering automation as baseline expectations, not optional habits. You are expected to model this yourself, continuously evaluate emerging AI engineering tools and ensure their effective adoption across the organization.

What You Will Do

Organizational and Technical Leadership

Act as the senior technical authority for day-to-day development decisions and as a trusted partner to the CTO on strategy and vision.

Lead the development group end to end and take ownership for the technical direction of the company’s platform in close collaboration with the CTO.

Set the standard for AI-native engineering practice across the development team: agentic workflows, LLM-assisted development and review, and copilot tooling as baseline expectations, not optional habits. You are expected to model this yourself and hold the bar for the team.

See around corners on technology choices, anticipating scaling and integration needs before they become blockers.

Own standards for code quality, testing and documentation across the development teams.

Delivery and Program Accountability

Own end-to-end delivery across the development team: planning, prioritization and execution against committed timelines.

Translate requirements from the Platform Architecture, Solution Architecture and product teams and with business and program goals into technical roadmaps and a clear, sequenced plan of work.

Carry functional accountability for platform delivery to major programs and data coordinating centres.

Track progress, raise risks early and keep delivery predictable and transparent.

Establish and refine processes (Agile or hybrid) that fit the team and the stage of the company.

Architecture and Hands-On Engineering

Work with the architecture teams to implement technical roadmap

Provide technical planning and resource allocation for development.

Stay technically current and go deep where it matters most: design, AI, critical-path work, complex problems and production issues.

Working with the CTO, security lead and other relevant team members, take the lead on technical architecture for AI integration into the company’s platform: retrieval-augmented generation, model serving, evaluation pipelines and responsible deployment of AI capabilities in a research and health data context.

Manage technical debt deliberately, balancing feature delivery against long-term maintainability.

Continuously improve the engineering development lifecycle, optimizing build performance, test execution, CI/CD pipelines and local development environments to increase developer productivity and delivery efficiency.

Drive automation across development, testing, deployment and operational workflows, eliminating repetitive manual tasks and enabling engineers to focus on high-value work.

Engineering Excellence and Developer Experience

Build and evolve internal engineering platforms, shared libraries, frameworks and self-service capabilities that improve consistency, reduce duplication and accelerate software delivery.

Continuously evaluate, adopt and optimize AI-assisted engineering tools, agentic workflows and intelligent automation that measurably improve developer productivity, software quality and delivery speed.

Define engineering standards and best practices for the effective, secure and responsible use of AI throughout the software development lifecycle, including code generation, testing, documentation, code review and operational support.

Drive automation across development, testing, deployment and operational workflows, leveraging AI where appropriate to eliminate repetitive manual work and enable engineers to focus on higher-value technical challenges.

Establish engineering documentation standards, leveraging AI-assisted documentation where appropriate, to ensure architecture, APIs, engineering practices, operational procedures and development workflows are accurate, discoverable and maintained.

Operations and Reliability

Build a team culture where operational risk is identified and addressed before it surfaces as a client incident: instill norms of proactive diagnosis, solution ownership and clear escalation, not problem-passing.

Partner with Security and Cloud Operations on incident response, root cause analysis and the closing of operational gaps before they surface as incidents for clients.

Hold responsibility for the Development teams’ contribution to platform quality and reliability.

Product, Client and Executive Collaboration

Partner with product and leadership to define the roadmap and make scope and sequencing trade-offs.

Represent engineering in client, partner and internal meetings, translating between technical and non-technical audiences.

Be a dependable, senior point of accountability for engineering commitments across the company.

What We Are Looking For

Required

10-15+ years in software engineering, including substantial time owning architecture and several years leading and managing engineering teams.

Has run an engineering team or function end to end, with full accountability for delivery, quality, people and operations.

Expert, hands-on technical depth: a strong coder and systems architect whom engineers trust and who can go deep when it counts.

Demonstrated ability to design systems that scale, and to see around corners on architecture and integration.

You have shipped LLM-integrated features, you work with agentic coding tools as a matter of course, and you can architect AI capabilities that are reliable, observable and auditable in a regulated data environment.

Real experience in a technology start-up or comparable fast-paced, high-ownership environment.

Broad modern-stack fluency: web (JavaScript and TypeScript with React, server-side (Python, Java) and relational data (PostgreSQL) at scale.

Solid grounding in cloud architecture (AWS and GCP), RESTful APIs, CI/CD and observability practices, enabling effective collaboration with Security & Cloud and Release Engineering counterparts.

Demonstrated success improving engineering effectiveness through developer tooling, CI/CD optimization, automation, documentation and AI-assisted development practices.

Legally authorized to work in Canada.

Strongly Preferred

Experience scaling a development group through a high-growth SaaS inflection point: past initial product-market fit, into multi-program, multi-client complexity.

Background in health care, life sciences, research data or another regulated, compliance-driven domain.

Familiarity with data engineering and integration patterns (ETL and ELT, BPMN workflow engines such as Camunda, event-driven systems, messaging).

Hands-on with containerization and orchestration (Docker, Kubernetes), infrastructure as code (Terraform) and observability tooling (Datadog or Splunk).

Familiarity with secure research or compute environments and authentication frameworks such as OpenOnDemand.

Experience leading engineering teams across multiple time zones or geographies.

Technical Environment

Frontend:

React, TypeScript, JavaScript

Backend:

Python, Java

Data:

PostgreSQL, ETL and ELT pipelines, BPMN workflow engines (Camunda), structured and semi-structured formats (JSON, CSV, XML, Parquet, Avro).

Cloud, infrastructure and operations:

AWS and GCP, Terraform, Docker, Kubernetes, Datadog observability, CI/CD.

Research compute:

RStudio, Jupyter, MATLAB, Apptainer (Singularity), DataLad, GPU-enabled workloads.

What the company’s Offers

Competitive salary with a performance bonus tied to delivery and team outcomes.

Group benefits plan.

Group retirement savings plan with a 2% employer match.

Professional development budget.

Hybrid work for the Montreal-based team, in office Tuesday through Thursday.

A senior leadership seat with full ownership of the development group and a direct line to the CTO and executive team.

The chance to shape the architecture and the team behind a platform used by thousands of researchers across North America and Europe.

Apply About employer

More about this job

Responsibilities

Lead the engineering group and own the platform’s technical direction, architecture, delivery, quality, and reliability in partnership with the CTO and other teams. Establish AI-native engineering practices, improve developer productivity and operational processes, and represent engineering in product, client, and executive discussions.

Requirements

Requires 10–15+ years of software engineering experience, substantial architecture ownership, and several years leading engineering teams with end-to-end accountability. Candidates should have hands-on expertise in modern software and cloud technologies, shipped LLM-integrated features, experience with AI-assisted development, and authorization to work in Canada; regulated-domain and high-growth SaaS experience are preferred.

Skills

Engineering Leadership
Software Architecture
Team Management
AI Integration
LLM-Integrated Features
Agentic Coding Tools
React
TypeScript
JavaScript
Python
Java
PostgreSQL
AWS
GCP
CI/CD
Kubernetes

Benefits

Performance Bonus
Group Benefits Plan
Group Retirement Savings Plan With 2% Employer Match
Professional Development Budget
Equity
Hybrid Work

Visa sponsorship

Not detected in the job text

Keywords

SaaS
Research Data Management
Software Engineering
Engineering Leadership
Technical Architecture
AI-Native Engineering
LLM
Retrieval-Augmented Generation
Agentic Workflows
React
TypeScript
JavaScript
Python
Java
PostgreSQL
AWS
GCP
RESTful APIs
CI/CD
Observability
ETL
ELT
Camunda
Docker
Kubernetes
Terraform
Datadog
Agile
Data Integration
Regulated Data

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