AI Engineering Lead (Permanent)

Toronto, ON
Hybrid
Posted Aug 11, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Lead · 10+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week

Job summary

Define and execute the long-term technical strategy for AI-driven business solutions while leading the architecture and development of scalable, real-time AI systems. You will mentor a team of engineers and collaborate with business stakeholders to align AI initiatives with insurance business goals.

Job details

CoreFactor is searching for an AI Engineering Lead on a full-time/permanent basis for one of our clients in the GTA. This position is hybrid and requires the successful incumbent to be in the office three (3) times per week. 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. Requirements 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.

What you’ll do

Requirements

Requires a bachelor's or master's degree in a technical field and 8+ years of experience in a technology-focused role. Candidates must have extensive hands-on experience building and deploying production-grade AI applications and fraud detection systems.