AI Engineering Lead

Definity Insurance Company • Toronto, ON

30d • Hybrid

About The Position

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 a AI
Engineering lead specializing in Fraud and Risk Intelligence, you will serve as
a technical authority and strategic leader in developing and deploying
sophisticated AI-powered solutions to combat fraud across our Property &
Casualty (P&C) insurance landscape. This lead role demands a visionary approach
to identifying and mitigating emerging fraud trends through the strategic
application of advanced AI. You will be instrumental in solutioning and leading
the implementation of our next-generation fraud detection systems, mentoring a
team of talented engineers, and setting technical directions 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.

What to expect

Strategic Fraud AI Leadership: Define and execute the long-term technical
strategy for AI-driven fraud detection and prevention. Lead the solutions and
development of scalable, real-time fraud detection systems, from
conceptualization to production.

Advanced AI Enablement & Integration: Spearhead the design and implementation
of cutting-edge AI Application by integrating machine learning models
(including LLMs, graph neural networks, and anomaly detection algorithms)
tailored for complex fraud scenarios.

System Architecture & Ownership: 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.

Mentorship & Technical Guidance: 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.

Cross-Functional Strategy & Influence: Collaborate with senior leadership,
underwriting, claims, and legal teams to align AI fraud initiatives with
overarching business goals. Translate complex fraud-related business problems
into actionable technical strategies.

Responsible AI in Fraud Detection: Champion and enforce the highest standards
of Responsible AI, ensuring all fraud models and systems are fair,
transparent, explainable, and fully compliant with regulatory requirements.
You will lead agentic red-teaming practices to identify and mitigate model
vulnerabilities.

Innovation & Research: Stay at the forefront of academic and industry
advancements in AI for fraud detection. Drive innovation by prototyping and
integrating novel techniques and technologies to stay ahead of fraudulent
actors.

What you bring

Expert Programming Skills: Mastery of Python and deep experience with AI/ML
frameworks (e.g., TensorFlow, PyTorch, ..). Proven ability to write clean,
high-performance, and maintainable code in Python, Java, SQL, and Spark.
AI & Machine Learning Mastery: Deep expertise in a wide range of AI/ML
techniques, with a specialization in anomaly detection, pattern recognition,
and predictive modeling in adversarial contexts. Extensive, hands-on
experience building and deploying LLM applications, RAG pipelines, and
agent-based workflows for fraud detection.
Data Expertise: A profound understanding of complex data structures, advanced
data modeling, and the management of both structured (e.g., claims history,
policy data) and unstructured (e.g., investigation notes, documents, images,
audio) data at scale.
Cloud Architecture: 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, API & Microservice Architecture: Proven experience designing and
implementing sophisticated AI integration patterns, implementing scalable,
event-driven microservice ecosystems. Expert-level proficiency in designing
and governing API-first strategies to ensure seamless, secure, and
high-performance integration between AI services and core enterprise
platforms.Experience in Building MCP and A2A servers/protocols.
Advanced Dev/MLOps: Expertise in Dev/MLOps best practices and tools,
including advanced containerization with Docker and Kubernetes, CI/CD for
machine learning, and AI observability.
Responsible AI: Authoritative knowledge of the principles and best practices
for building ethical, fair, and transparent AI systems, with specific
experience in applying these to fraud detection.

Soft Skills

Strategic Problem-Solving: Ability to analyze multifaceted business problems
within the insurance fraud domain and architect innovative, effective
AI-driven solutions.
Leadership & Communication: Exceptional communication and collaboration
skills, with a proven ability to mentor team members and articulate complex
technical strategies to executive-level stakeholders.
Innovation & Vision: A passion for staying ahead of the curve in AI and a
demonstrated ability to identify and champion opportunities for innovation
that provide a competitive advantage.

Experience

A bachelor’s or master’s degree in computer science, 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 cases.
Significant experience leading the design and implementation of large-scale
AI projects from start to finish.
P&C Insurance and Fraud Domain Expertise: Deep familiarity with core
insurance processes, particularly claims management and underwriting, and
extensive knowledge of fraud detection techniques are highly desirable.

Requirements

• Mastery of Python and deep experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, ..).
• 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, with a specialization in anomaly detection, pattern recognition, and predictive modeling in adversarial contexts.
• Extensive, hands-on experience building and deploying LLM applications, RAG pipelines, and agent-based workflows for fraud detection.
• A profound understanding of complex data structures, advanced data modeling, and the management of both structured (e.g., claims history, policy data) and unstructured (e.g., investigation notes, documents, images, audio) data at scale.
• Extensive hands-on experience architecting and deploying scalable AI solutions on a major cloud platform (Google Cloud or AWS).
• Proven experience designing and implementing sophisticated AI integration patterns, implementing scalable, event-driven microservice ecosystems.
• Expert-level proficiency in designing and governing API-first strategies to ensure seamless, secure, and high-performance integration between AI services and core enterprise platforms.Experience in Building MCP and A2A servers/protocols.
• Expertise in Dev/MLOps best practices and tools, including advanced containerization with Docker and Kubernetes, CI/CD for machine learning, and AI observability.
• Authoritative knowledge of the principles and best practices for building ethical, fair, and transparent AI systems, with specific experience in applying these to fraud detection.
• Ability to analyze multifaceted business problems within the insurance fraud domain and architect innovative, effective AI-driven solutions.
• Exceptional communication and collaboration skills, with a proven ability to mentor team members and articulate complex technical strategies to executive-level stakeholders.
• A passion for staying ahead of the curve in AI and a demonstrated ability to identify and champion opportunities for innovation that provide a competitive advantage.
• A bachelor’s or master’s degree in computer science, 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 cases.
• Significant experience leading the design and implementation of large-scale AI projects from start to finish.

Nice To Haves

• Deep experience with Google Cloud, including Vertex AI and Gemini
• Deep familiarity with core insurance processes, particularly claims management and underwriting, and extensive knowledge of fraud detection techniques are highly desirable.

Responsibilities

• Define and execute the long-term technical strategy for AI-driven fraud detection and prevention.
• Lead the solutions and development of scalable, real-time fraud detection systems, from conceptualization to production.
• Spearhead the design and implementation of cutting-edge AI Application by integrating machine learning models (including LLMs, graph neural networks, and anomaly detection algorithms) tailored for complex fraud scenarios.
• 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 legal teams to align AI fraud initiatives with overarching business goals.
• Translate complex fraud-related business problems into actionable technical strategies.
• Champion and enforce the highest standards of Responsible AI, ensuring all fraud models and systems are fair, transparent, explainable, and fully compliant with regulatory requirements.
• Lead agentic red-teaming practices to identify and mitigate model vulnerabilities.
• Stay at the forefront of academic and industry advancements in AI for fraud detection.
• Drive innovation by prototyping and integrating novel techniques and technologies to stay ahead of fraudulent actors.

Benefits

• Hybrid work schedule for most roles
• Company share ownership program
• Incentive Program - Eligible employees may participate in various incentive plans which are paid out at the discretion of the company and subject to individual and company performance.
• Pension and savings programs, with company-matched RRSP contributions
• Paid volunteer days and company matching on charitable donations
• Educational resources, tuition assistance, and paid time off to study for exams
• Focus on inclusion with employee groups, support for gender affirmation surgery, access to BIPOC counsellors, access to programs for working parents
• Wellness and recognition programs
• Discounts on products and services

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees