AI model risk governance leader developing enterprise frameworks, standards, and training for responsible AI at global financial services provider Manulife. Hybrid role partnering with regulated - industry stakeholders.
About the role
- Manager leading applied AI science for UBC’s pharmaceutical support and healthcare solutions. Developing, evaluating, and governing reusable AI capabilities while managing Applied AI Scientists.
Responsibilities
- Lead, mentor, and develop a small team of Applied AI Scientists and provide technical and scientific guidance across their work
- Design, develop, and refine reusable AI capabilities using machine learning, large language models, retrieval-augmented generation, AI agents, and other approved enterprise AI technologies
- Design solutions combining models, prompts, context, retrieval, tools, structured outputs, human review, and workflow integration for defined intended uses
- Design and execute evaluations using representative datasets, reference standards, performance metrics, acceptance criteria, and statistical methods
- Define expected behavior, analyze outputs and failure modes, assess uncertainty and limitations, and recommend improvements based on evaluation evidence
- Develop maintainable Python code, analytical workflows, evaluation tools, and reusable software components supporting AI development and testing
- Collaborate with AI Architecture, Product Management, application teams, subject matter experts, Quality, and Governance
- Stay current on advances in artificial intelligence, machine learning, statistics, and evaluation methods
- Contribute to evolving practices within the AI Center of Excellence
- Hire, mentor, direct, and manage the performance of 2–5 Applied AI Scientists
Requirements
- Master's degree in Computer Science, Data Science, Statistics, Biomedical Engineering, Applied Mathematics, Computer Engineering, or a related quantitative discipline
- Bachelor's degree in a related quantitative discipline with significant applied AI, machine learning, or statistical experience will also be considered
- 5+ years of experience developing AI, machine learning, data science, or applied AI solutions in applied environments
- Must have Healthcare/CRO experience
- Familiarity with GxP, 21 CFR Part 11, HIPAA, GDPR, software validation, or related regulated-system expectations
- Strong programming experience using Python, R, or a comparable language
- Experience mentoring technical staff, leading scientific work, or providing technical direction across projects
- Experience applying statistical methods, experimental design, or performance analysis to complex technical problems
- Experience defining AI evaluation metrics, assessing the effectiveness of AI controls, and developing monitoring approaches for AI system performance and risk
- Experience collaborating with software engineers, architects, product teams, and business stakeholders throughout the AI development lifecycle
- Strong understanding of statistics, experimental design, sampling, machine learning, model validation, uncertainty, bias, and generalizability
- Experience developing capabilities using large language models, retrieval-augmented generation, prompt and context design, AI agents, tool integration, and structured outputs
- Experience developing evaluation datasets and reference standards, selecting appropriate metrics, defining acceptance criteria, and analyzing performance and failure modes
- Strong programming skills with the ability to develop maintainable analytical software, AI capabilities, and evaluation tooling
- Understanding of how models, data, retrieval, prompts, tools, human review, and workflow context combine to shape AI system behavior
- Ability to document and communicate evaluation methods, assumptions, results, uncertainty, limitations, and recommendations
- Ability to connect technical decisions to enterprise architecture, long-term reuse, scalability, and business strategy
- Ability to translate operational needs and workflows into structured AI capabilities and measurable evaluation questions
- Advanced ability to resolve complex architecture and engineering challenges through practical and maintainable solutions
- Ability to communicate architectural concepts, tradeoffs, and recommendations clearly to executives, engineers, scientists, architects, and business stakeholders
- Ability to work effectively across Product Management, AI Science, Application Development, Platform Engineering, DevOps, Security, Data, Quality, and business teams
- Ability to evaluate emerging technologies and evolve architectural direction while maintaining engineering discipline and operational reliability
Benefits
- Competitive salaries
- Growth opportunities for promotion
- RRSP with company match*
- Tuition reimbursement
- Flexible work environment
- Discretionary PTO (Paid Time Off)
- Paid Holidays
- Employee assistance programs
- Medical, Dental, and vision coverage
- Telemedicine (Virtual doctor appointments)
- Wellness program
- Adoption assistance
- Short term disability
- Long term disability
- Life insurance
- Discount programs
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