AI Engineer, Asset Management

Manulife • Boston, MA

1d • Hybrid

About The Position

Manulife Wealth and Asset Management is seeking a motivated and dedicated AI Engineer with a focus on Investment Management Applications, data engineering, tooling, and standards development. In this key role, you will be responsible for collaborating with front office investment teams to develop AI solutions, sourcing investment market and portfolio data, developing data pipelines, prototype development of AI applications, maintaining and enhancing Python libraries, lightweight applications, and supporting architecture and scale efforts. You will also contribute to the development of tools and standards to operationalize LLM and Generative AI use-cases, ensuring seamless integration with existing MLOps practices and infrastructure. Position Responsibilities: Collaboration and Support: Work with front office analysts and portfolio managers to identify AI/ML project opportunities, develop lightweight prototypes, and implement key capabilities in a microservices framework. Lead data model design and implementation within the Asset Management AI group. Support automated data mapping, cataloging, and data quality testing prior to hand off to division data team for production Monitor daily data quality checks, support internal teams on reconciliation and remediation as needed. Standards Development: Contribute to defining and implementing effective practices and standards for MLOps processes to ensure efficient and streamlined operations. CI/CD Pipeline Management: Assist in implementing and managing CI/CD pipelines to automate testing and deployment processes, ensuring efficient and reliable operations. Industry Insights: Stay updated with industry advancements in LLM and Generative AI models, enhancing MLOps capabilities to support LLM Ops needs. Collaborate with the information technology group to understand, align, and inform standards and governance to support data quality in CI/CD workflows in a DevSecOps framework. Support near term future state projects to improve ETL, compute, storage, and hosting in Azure using tools such as Databricks, Kubernetes, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics (AWS, Google Cloud Equivalents ok as well). When you join our team: 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. #LI-Hybrid 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 https://www.manulife.com/en/about/our-story.html. 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 [email protected].

Requirements

• PhD, Masters or equivalent experience in Computer Science, Data Science, Statistics, or a related field.
• CFA Charter or demonstrated progress
• Data engineering experience in an investment context.
• 1-2 years of experience in building and maintaining AI infrastructure and tooling.
• Proficiency in Python and experience with developing libraries and applications.
• Experience with CI/CD tools and pipelines
• Familiarity with cloud platforms (preferably Azure), ML development environments (Databricks), and containerization technologies (Docker, Kubernetes).
• Exposure to experiment tracking tools (e.g., MLFlow) and monitoring solutions.
• Strong communication skills, able to explain complex concepts to various collaborators.
• Basic understanding of the machine learning lifecycle and standard methodologies in MLOps.
• Basic understanding of LLM/GenAI models and their operational requirements.

Nice To Haves

• Experience working with investment data, including understanding of security characteristics, propagation up and down the hierarchy, and the impact of corporation actions.
• Experience in deploying and maintaining RAG pipelines and working with vector databases like MongodB/ LancedB.
• Experience developing within an agentic framework, using Langgraph, Semantic Kernel, etc.
• Proven success with ETL Development, schema management, API design, data operations, and data architecture.
• Understanding of the research process showcased by at least one publication
• Databricks Ecosystem Expertise: Hands-on expertise in the Databricks ecosystem, particularly model management using Unity Catalog.
• Full Stack Engineering Exposure: Ability to build proof of concepts/demos including both front-end and back-end development.
• Adaptability: Demonstrated proficiency in quickly picking up new frameworks and libraries.

Responsibilities

• Work with front office analysts and portfolio managers to identify AI/ML project opportunities, develop lightweight prototypes, and implement key capabilities in a microservices framework.
• Lead data model design and implementation within the Asset Management AI group.
• Support automated data mapping, cataloging, and data quality testing prior to hand off to division data team for production
• Monitor daily data quality checks, support internal teams on reconciliation and remediation as needed.
• Contribute to defining and implementing effective practices and standards for MLOps processes to ensure efficient and streamlined operations.
• Assist in implementing and managing CI/CD pipelines to automate testing and deployment processes, ensuring efficient and reliable operations.
• Stay updated with industry advancements in LLM and Generative AI models, enhancing MLOps capabilities to support LLM Ops needs.
• Collaborate with the information technology group to understand, align, and inform standards and governance to support data quality in CI/CD workflows in a DevSecOps framework.
• Support near term future state projects to improve ETL, compute, storage, and hosting in Azure using tools such as Databricks, Kubernetes, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics (AWS, Google Cloud Equivalents ok as well).

Benefits

• Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level