AI Engineering Lead
At a glance
Senior AI Engineering role at Hdks. Toronto · full-time · CA$108,700–CA$158,700 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the technical direction for AI solutions and lead their design, build and rollout across property and casualty insurance
- Build scalable, real-time systems using machine learning, including large language models, graph neural networks and computer vision
- Own the fraud platform end to end, from preparing its data through deploying models into production
- Guide AI engineers and data scientists, while advising leadership and business teams on turning insurance needs into technical plans
- Test emerging AI and data engineering methods, then prototype and integrate useful approaches
What you bring
- At least eight years in a technology-focused role, including three years hands-on building and deploying production fraud applications
- Strong Python skills and practical command of AI/ML methods, frameworks and production application development
- Experience designing and deploying scalable AI systems on Google Cloud or AWS, including RAG pipelines or agent-based workflows
- A bachelor's or master's degree in computer science, engineering, data science, AI or a related field
Who this fits
This senior technical lead role suits someone who wants to shape AI architecture while mentoring engineers and data scientists. The work centers on property and casualty insurance, including fraud, underwriting, pricing, claims and customer experience. The role is based in Toronto, Canada.
From the employer
The Opportunity
We are seeking a forward-thinking AI Engineering Lead to join our innovative team and drive the future of Property & Casualty (P&C) insurance. As an AI Engineering Lead, you will serve as a technical authority and strategic leader in developing and deploying sophisticated AI-powered solutions to drive business value and innovation across the P&C insurance value chain.
You will be instrumental in architecting and leading the implementation of our next-generation AI and data platforms, mentoring a team of talented engineers, and setting the technical direction for AI in this critical domain. You will be at the forefront of technological innovation, leveraging your expertise in data, AI models, and responsible AI to create impactful and scalable applications across underwriting, pricing, claims, and customer experience.
What to Expect
- Define and execute the long-term technical strategy for AI-driven business solutions. Lead the architecture and development of scalable, real-time AI systems that address key challenges and opportunities in P&C, from conceptualization to production.
- Spearhead the design and implementation of cutting-edge AI solutions using machine learning models (including LLMs, graph neural networks, and computer vision) tailored for key insurance business problems.
- As the tech owner of our AI fraud prevention platform, you will Oversee the entire workflow from collecting and preparing data to putting models into production.
- Act as a lead and mentor to other AI engineers and data scientists. Provide expert technical guidance on complex projects, foster a culture of innovation, and elevate the team's capabilities in building robust AI solutions.
- Collaborate with senior leadership, underwriting, claims and other business and product teams to align AI initiatives with overarching business goals. Translate complex business problems into actionable technical strategies.
- Stay at the forefront of academic and industry advancements in AI and data engineering. Drive innovation by prototyping and integrating novel techniques and technologies to maintain a competitive edge.
What you Bring
- Mastery of Python and deep experience with AI/ML frameworks, Proven ability to write clean, high-performance, and maintainable code in Python, Java, SQL, and Spark.
- Deep expertise in a wide range of AI/ML techniques. Extensive, hands-on experience building and deploying AI based applications, RAG pipelines, and agent-based workflows.
- Extensive hands-on experience architecting and deploying scalable AI solutions on a major cloud platform (Google Cloud or AWS). Deep experience with Google Cloud, including Vertex AI and Gemini, is a significant asset.
- AI Integration: Experience designing and working with A2A, MCP, Agentic RAG, and including conventional microservices, and event-drive architecture.
- A bachelor's or master's degree in computer science, or Computer/Software Engineering, Data Science, Artificial Intelligence, or a related field; a Ph.D. is a plus.
- 8+ years of experience in a technology-focused role, with a minimum of 3 years of proven, hands-on experience in building and deploying production-grade fraud use.
Salary Range: $108,700-$158,700