Head of Engineering
REMOTE /
Toronto, Ontario, Canada
- Permanent
This job allows you to work remotely
Job Description
* Toronto is the primary preferred location. Montreal is the second. Third could be across Canada.
Company Profile
Our client is a venture-backed AI software company building advanced workflow automation and computer vision products for highly technical industries. They are scaling rapidly and looking for a hands-on Head of Engineering to help lead the next phase of growth.
This is not a traditional corporate VP Engineering role. The company is looking for a builder and player-coach who can scale engineering execution while remaining technically credible with a highly senior team.
The Head of Engineering will work closely with the CEO, Product leadership, and engineering leads to improve delivery velocity, platform reliability, technical execution, and organizational scalability. This individual will help shape both the technical direction and operational maturity of the engineering organization while contributing hands-on where needed.
Key Responsibilities
- Align Engineering, Product, and GTM teams through strong planning, prioritization, and execution processes
- Own engineering delivery, operational quality, and technical execution across the platform
- Lead architectural discussions and guide scalable cloud-native platform decisions
- Improve engineering velocity through better developer tooling, CI/CD, automation, observability, testing, and release processes
- Drive reliability, scalability, security, and technical quality standards across systems and teams
- Support production AI/ML systems, integrations, and platform reliability initiatives
- Mentor engineering leads and emerging managers while helping scale the organization through hiring, onboarding, coaching, and operational structure
- Help establish a high-performance engineering culture focused on accountability, ownership, autonomy, and execution
- Partner closely with executive leadership on technical strategy, roadmap planning, prioritization, and organizational growth
- Remain hands-on where needed through architecture reviews, technical guidance, debugging, code reviews, and engineering support
Must Have Skills:
- Proven experience scaling engineering organizations within high-growth SaaS, AI, or startup environments, ideally 0-1 type of scale.
- Strong background leading cloud-native distributed systems and modern SaaS architectures
- Experience building or supporting production AI/ML systems and workflows
- Strong technical fluency across modern engineering stacks including Python, Node.js/TypeScript, React, cloud infrastructure, and modern development tooling
- Deep understanding of CI/CD systems, observability, testing strategies, platform reliability, and engineering operational best practices
- Experience improving engineering throughput, execution quality, and developer productivity
- Strong people leadership experience including hiring, mentoring, coaching, and organizational development
- Comfortable operating in fast-moving startup environments with high ownership and ambiguity
- Strong communication skills with the ability to work effectively across engineering, product, executive, and customer-facing conversations
- Willingness to remain technically engaged and hands-on as needed
Nice to Have Skills:
Experience working within AI-native product organizations
Exposure to computer vision, multimodal AI, or workflow automation products
Experience leading engineering organizations through rapid scale-up phases
Founder, startup CTO, or early-stage technical leadership experience
Experience implementing AI-assisted development workflows and engineering productivity tooling
Exposure to highly visual or collaborative product environments
Experience managing distributed engineering teams across multiple functions or pods
Domain Exposure: Prior experience within automated estimation spaces, industrial blueprints, complex spatial modeling, or CAD-adjacent software environments (e.g., Autodesk, Miro, Figma ecosystems).
Advanced Technology Stack: Background working in product environments centered around computer vision, data pipelines, or automated document processing.