Why This Job is Featured on The SaaS Jobs
This Head of AI Engineering role sits at the intersection of applied AI and core SaaS product development, with a clear mandate to turn research-grade machine learning into customer-facing capability. The emphasis on “next generation” AI-driven solutions and an incubation remit signals work that is closer to platform creation than incremental feature delivery, which is a meaningful theme in today’s SaaS landscape as AI becomes a product layer rather than an add-on.
From a SaaS career perspective, the role offers exposure to the full lifecycle that many AI initiatives struggle with: moving from experimentation to reliable production systems, then operating them at scale. Building ML infrastructure, shipping agentic applications, and establishing practices around data quality and monitoring are transferable skills across modern SaaS companies, particularly those integrating AI into their core value proposition and needing repeatable delivery patterns.
This position is best suited to a senior, hands-on technical leader who is comfortable acting as a player-coach while shaping an engineering function. It will appeal to professionals who value close collaboration with founders, enjoy setting technical direction under ambiguity, and want accountability for measurable outcomes rather than isolated R&D output.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
The Role:
We're looking for an Engineering Leader with a Data Science / Machine Learning background to head the incubation of CommerceIQ’s next generation of AI-driven SaaS solutions. The Head of AI Engineering is both hands-on and leadership-focused: you will act as a player-coach, directly shaping the technical architecture of our AI platform while building and mentoring a team of engineers.
You will report directly to our cofounders to design and deliver advanced AI and agentic applications that push the boundaries of what is possible in applied AI for commerce. You will be accountable for scaling AI systems from research through production, ensuring that they create measurable business impact for the world’s largest brands.
This role is ideal for a technical leader who has both trained models and shipped them into production, built agentic applications, and has a deep understanding of machine learning systems at scale.
This is a remote role based out of Toronto. Please note that we are only considering candidates located in the Toronto area for this role.
What You'll Do:
- Partner directly with the cofounders to set and execute the AI engineering strategy.
- Hire, lead, and mentor a founding AI engineering team within our incubation group, growing both technical depth and organizational capability.
- Act as a player-coach: contribute hands-on to architecture, model training, and backend engineering while scaling a team around you.
- Design and build scalable ML infrastructure to support model training, fine-tuning, deployment, and monitoring at production scale.
- Lead the development of agentic applications, including designing, training, and launching agents that operate in real-world customer environments.
- Establish best practices for data quality, labeling, and ML pipelines, enabling rapid experimentation and continuous improvement.
- Drive responsible AI development by ensuring reliability, ethics, safety, and performance in all models and agents shipped to production.
- Collaborate closely with product, data science, and business stakeholders to translate research breakthroughs into customer-facing features.
- Set engineering standards and build a culture of technical excellence, innovation, and accountability.
What You'll Bring:
- 5+ years of experience in backend software engineering, with 2+ years leading AI/ML teams.Hands-on experience training AI/ML models, including foundation models, fine-tuned models, or specialized domain models.
- Proven experience building and deploying agentic applications, with deep knowledge of agent design patterns and orchestration.
- Strong track record of launching AI models and agents into production environments at scale.
- Advanced expertise in machine learning, deep learning, and reinforcement learning.
- Experience designing scalable data systems and pipelines for training and inference.
- Fluency in backend and ML-oriented programming languages such as Python, Java, Scala, or C++.
- Knowledge of modern ML toolkits and frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, Ray, etc.).
- Strong ability to balance hands-on technical depth with leadership, mentoring, and organizational building.
- Excellent communication and influencing skills, with experience working directly with senior executives or founders.
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
Check out our LinkedIn page to learn more about what it’s like to work at CommerceIQ!
