Lead Data AI Architect - Manulife, Toronto is listed at Manulife in Toronto, ON. The Beaver Board aggregates this opening from the employer's career page — apply using the button below to reach the official application. Browse more jobs at Manulife.
job description
AI Summary
This Lead Data AI Architect role at Manulife in Toronto focuses on translating business strategy into secure, scalable data and AI architectures. Key duties include defining reference architectures and reusable patterns for data, ML, and GenAI, and guiding delivery teams. Top requirements include over 10 years of data/analytics architecture experience, with at least 3 years designing AI/ML solutions, and a strong understanding of data governance.
About the Role at Manulife
This senior role at Manulife involves leading the end-to-end architecture for modern data and AI solutions, encompassing enterprise data lakes, data warehouses, streaming analytics, machine learning, and Generative AI (GenAI) products. The Lead Data AI Architect will be instrumental in defining and evangelizing reference architectures and reusable patterns for data, ML, and GenAI, including MLOps, LLMops, and AIOps, while providing essential guidance to delivery teams on their implementation. A core responsibility is to stay current with emerging technologies and practices across data engineering, machine learning, and GenAI, such as RAG, vector search, and model fine-tuning. This position ensures interoperability, data consistency, and responsible AI through robust API and data standards, metadata management, security-by-design principles, privacy, and comprehensive model governance. The architect will also conduct discovery to understand Manulife's current-state data and AI landscapes, including platforms, pipelines, models, and key use cases, ensuring all solution architectures align with business strategy and enterprise technology standards. This role is crucial for expanding and governing a catalogue of reusable patterns for data, ML, and GenAI to promote consistency, efficiency, and adherence to best practices within Manulife.
Key Responsibilities and Expertise
The Lead Data AI Architect at Manulife is expected to create and continuously refine target data and AI reference architectures, primarily utilizing Azure services to achieve optimal performance, scalability, security, and cost efficiency. This involves evaluating and integrating Azure-native and partner technologies that enhance data processing, storage, analytics, and the entire AI model lifecycle management, including CI/CD, testing, monitoring, and cost controls. A significant part of the role is to identify and recommend opportunities to improve platform reliability, observability, data quality, model performance, and cost optimization across Manulife's data and AI initiatives. The architect will partner closely with engineering, product, data science, security, and risk teams to enable the adoption of data and AI patterns, providing critical architecture guidance throughout the delivery process. Maintaining architecture documentation standards, ensuring accessibility, version control, and compliance, is also a key duty, alongside managing a centralized repository for data and AI architecture artifacts, including standards, reusable patterns, and governance decisions. This role demands strong architecture leadership skills to drive decisions, manage trade-offs, and influence various teams while maintaining a keen focus on delivery.
Qualifications and Professional Growth
Candidates for this Lead Data AI Architect position at Manulife should possess over 10 years of experience in data and analytics architecture, with at least 3 years specifically designing AI/ML solutions in production environments. Experience with GenAI is strongly preferred, demonstrating a forward-thinking approach to artificial intelligence. A Bachelor’s degree in Computer Science, Engineering, Information Systems, Data/AI, or a related field is required, with a Master’s degree being preferred. Proven experience architecting on Azure across data and AI services, such as Data Lake, Databricks, Synapse, and Fabric, ideally within financial services or insurance, is essential. A strong understanding of data governance, data modelling, integration, metadata management, and privacy/security controls is critical, along with the ability to extend these practices to comprehensive AI and GenAI governance. Excellent communication and stakeholder management skills are vital for translating complex data and AI concepts for both technical and non-technical audiences across Manulife. Experience with modern engineering practices like Infrastructure as Code (IaC) and CI/CD, as well as MLOps/LLMops concepts, including model/prompt versioning, evaluation, monitoring, and deployment patterns, is also required. Manulife empowers its employees to learn and grow, fostering a flexible environment where well-being and inclusion are prioritized, supporting career development within a global team.
