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Salary
$168k – $217k per year
Location
Remote (Canada)
Seniority
Architect · 7+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director of Engineering, AI based in Canada.

This leadership opportunity is designed for an experienced engineering executive ready to shape and execute a platform-wide Artificial Intelligence strategy.

You will lead high-performing teams of AI and Machine Learning engineers and applied scientists building foundational capabilities used across a broad product portfolio.

The role combines technical strategy, architecture, engineering execution, organizational design, and senior-level talent development.

You will work closely with Product, Design, Data Science, Infrastructure, and other functions to translate AI opportunities into scalable products and measurable customer impact.

Your recent experience with generative AI, Large Language Models (LLMs), agentic systems, and foundation models will help guide technical direction and product innovation.

You will operate at significant scale, influencing complex roadmaps while balancing technical quality, business priorities, and long-term platform evolution.

This is an opportunity to serve as a senior AI and engineering leader while building teams and capabilities that shape the future of AI-powered products.

Accountabilities

    • Lead the AI engineering organization and build high-functioning teams of AI and Machine Learning engineers and applied scientists focused on delivering high-quality results.
    • Establish and execute a platform-wide AI and Machine Learning strategy aligned with product priorities, customer needs, and long-term business objectives.
    • Lead teams responsible for developing foundational AI and Machine Learning products and capabilities that can be leveraged across the broader product portfolio.
    • Partner with senior engineering leadership to define organizational strategy, establish new teams, develop sustainable team structures, and guide architecture and product direction.
    • Lead the development of highly scalable, reliable, and distributed AI products while ensuring strong engineering practices and consistent execution.
    • Guide teams through complex technical and product roadmaps, working closely with Product Management and Design to align strategy, priorities, and delivery.
    • Provide technical leadership across architecture, system design, engineering execution, AI product quality, and platform scalability.
    • Develop and maintain systems for deploying, managing, evaluating, and serving Machine Learning models and agentic products at scale.
    • Drive effective evaluation, quality, and model judgment practices across research-oriented AI initiatives and product engineering.
    • Recruit, coach, develop, and retain engineering leaders, applied scientists, and AI/ML engineers while establishing clear career paths and performance expectations.
    • Provide regular feedback and coaching to leaders and support performance reviews, career development, and organizational planning.
    • Partner across Engineering, Product, Design, Data Science, Infrastructure, Go-to-Market, Legal, and Support to remove organizational barriers and improve execution.
    • Participate in architectural decisions, quarterly planning, staffing strategy, roadmap development, and major product launches.
    • Balance technical debt, product features, bugs, and business priorities while keeping teams focused on the highest-impact opportunities.
    • Represent the organization as a subject matter expert in AI and Machine Learning, bringing relevant industry trends and emerging technologies into strategy and roadmap discussions.
    • Requirements

      • 7+ years of experience building and supporting products in production environments.
      • 7+ years of software development experience, including several years leading engineering teams and managing through other leaders.
      • Demonstrated success building sustainable, high-performing engineering organizations through hiring, coaching, organizational design, and leadership development.
      • Proven experience leading engineering teams that build Artificial Intelligence and Machine Learning or agentic products, including collaboration with or leadership of applied scientists and AI/ML engineers.
      • Recent, direct experience, typically within the last 2-3 years, leading or closely driving the development of modern AI products, agentic systems, or Large Language Model (LLM)-based products built on foundation models.
      • Strong understanding of AI product evaluation, quality, model judgment, and the challenges of translating research-oriented work into production-grade products.
      • Demonstrated ability to lead mixed teams of applied scientists and AI/ML engineers while supporting research-informed development and product engineering.
      • Experience scaling high-performance teams through the hiring and development of engineering leaders, applied scientists, and AI/ML engineers.
      • Experience within a Software-as-a-Service (SaaS) or product organization that has undergone a significant Artificial Intelligence transformation or shift in product direction is preferred.
      • Strong ability to establish a clear vision and align teams toward high-impact work across complex product portfolios serving diverse, global customers.
      • Proven ability to influence and align stakeholders across different functions and perspectives to drive successful outcomes.
      • Experience developing enterprise-scale distributed applications using technologies such as Python, Java, and distributed queuing systems.
      • Experience developing and scaling systems for Machine Learning model deployment, management, evaluation, and serving.
      • Experience with generative AI, including open-source and third-party solutions such as OpenAI.
      • Strong strategic thinking, communication, collaboration, and executive-level stakeholder management skills.
      • Pragmatic, adaptable, highly motivating leadership style with the ability to guide teams through ambiguity and rapidly changing AI technologies.
      • Benefits

        • Current hiring range of CA$232,000-CA$300,000 annually.
        • Broader base pay range of CA$232,000-CA$348,000, with individual compensation determined by geographic zone, relevant experience, skills, performance, and impact.
        • 100% employer-paid health benefits for eligible employees and dependents, including medical, dental, vision, life insurance, and disability coverage.
        • 25 days of annual vacation, plus 5 paid sick days, public holidays, and additional company-wide Rest & Recharge days.
        • Free access to mental health support, including coaching, therapy sessions, and digital wellness resources.
        • CA$950 annual Lifestyle Spending Account supporting physical, mental, and financial well-being.
        • One-time US$550 equivalent home-office setup stipend.
        • Monthly US$50 equivalent internet stipend.
        • Confidential, no-cost access to financial experts for personalized financial wellness support.
        • Subsidized childcare and eldercare options.
        • Employer matching for eligible charitable donations.
        • Remote work opportunity for candidates based in Alberta, British Columbia, or Ontario.
        • Opportunity to lead AI and Machine Learning strategy at significant product and organizational scale.
        • High-impact leadership scope spanning engineering, product, design, data science, infrastructure, and other functions.
        • Opportunities to shape AI capabilities, technical strategy, organizational growth, and long-term product direction.
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