Lead AI Platform Engineer

At Manulife, Cloud & AI Platform Engineer is responsible for designing, building, and maintaining the infrastructure necessary for deploying AI solutions on cloud platforms. This role involves creating scalable and efficient cloud architectures that support AI model training, deployment, and management. They collaborate closely with data scientists and data engineers to ensure seamless integration and operational efficiency of AI models. Additionally, the role requires monitoring system performance, troubleshooting issues, and continuously optimizing platforms for cost-effectiveness and scalability. Must stay informed about the latest advancements in AI and cloud technologies to drive innovation and improve the organization's AI capabilities. Partner with architects and development teams in understanding data and using it to serve our businesses and operations whilst ensuring alignment to Manulife’s IT security and risk guidelines!

This role is an individual contributor role at the senior technical leadership level. Along with deep technical hands-on experience, strong leadership capabilities are equally required.

Office location: Toronto - Canada or Waterloo - Canada

Work arrangement: Hybrid - 3 days in office, 2 days from home;

Remote working arrangement is not available.

Position Responsibilities:

• Design scalable and robust AI infrastructure that supports model training, deployment, and management

• Update and maintain AI models and infrastructure as technology and requirements evolve

• Stay updated with the latest advancements in AI and machine learning technologies

• Experiment with new tools and techniques to improve cloud data lake platform and models

• Gain deep understanding of data by collaborating with business and advanced analytics partners; demonstrate the understanding to design, curate and publish connected data sets that enables users to self-serve

• Lead on ensuring our Azure applications in prod run within SLA and ensure their robustness and security.

• Propose technology improvements or come up with innovative solutions to solve business problems.

• Participate and propose best solution for AI projects

• Collaborate with Architecture, security, and risk teams and implement latest guidelines and Azure standard methodologies

• Lead, mentor and guide data engineers to promote customer first approach

• Automate infrastructure provisioning and deployment using tools such as terraform

• Implement CI/CD pipelines that enables automated code deployment

• Participate in Agile sprints and ceremonies; supports rapid iteration and development

• Take lead in maintaining the inventory of critical data elements and lineage

• Cultivate and maintain strong relationships and fosters collaboration with various teams and partners within the organization

• Provide guidance and mentorship to junior engineers and other team members

Required Qualifications:

• Bachelor’s in Computer / IT or data related fields required

• Minimum 10+ years IT industry experience is required

• 7 to 10 years of previous platform engineering experience, with experience working in enabling azure related data technologies

• 1-2 years of experience in model deployments and infrastructure deployments for AI

• Solid understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection

• Strong hands-on knowledge of Azure Databricks, ADF, ADLS, Synapse Serverless/dedicated/spark pools, Python, PySpark, and T-SQL along with experience designing and developing scripts for ETL processes and automation in Azure Data Factory and Azure Databricks

• High proficiency in GIT/Jenkins/dev ops processes to maintain and resolve issues with data pipelines in production

• Good understanding of data modeling, data mart, data Lakehouse architecture, SCD, data mesh and delta lake overall

• Solid understanding of data privacy and compliance regulations and standard methodologies for preserving customer data

• Experience deploying LLM models & monitoring AI infrastructure in cloud environments

• Knowledge of implementing azure technologies and networking via terraform along with ability to fix issues with Azure infrastructure in production

Preferred Qualifications:

• Architectural background on solutioning and designing AI use cases is preferred

• Industry experience from large complex highly regulated environment is highly desired

• Master’s degree is a plus

• We’ll empower you to learn and grow the career you want.

• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.

• As part of our global team, we’ll support you in shaping the future you want to see.

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit .

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact .

Referenced Salary Location

CAN, Ontario, Toronto, 200 Bloor Street East

Working Arrangement

Hybrid

Salary range is expected to be between

$113,260.00 CAD - $210,340.00 CAD

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact for the salary range for your location.

Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact for more information about U.S.-specific paid time off provisions.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our .