Senior Applied AI Engineer – GenAI & Actuarial Systems

Manulifes Group Functions AI team is scaling AI and advanced analytics capabilities for Actuarial partners to improve how decisions are made and how insights are generated! This role sits within the AI team and focuses on building solutions that use machine learning optimization and modern analytical approaches to solve actuarial-adjacent problems at enterprise scale.

In this role you will take actuarial problems and translate them into AI use cases. These include predictive risk and behavior modeling grouping outlier identification scenario and sensitivity engines and automation of controls and analytical routines across recurring cycles. The emphasis is on building reusable production-ready components and analytical products that integrate into business workflows with clear explainability strong evaluation ongoing monitoring and governance-ready evidence!

Position Responsibilities:
You will work closely with actuarial collaborators and engineering partners. Together you will deliver solutions that are explainable robust and operationally balanced. These solutions help accelerate decision cycles improve consistency and let teams focus on higher-value judgment where it matters.

Own end-to-end solution design for actuarial AI

• Translate actuarial business problems into a clear solution approach: business workflow data flow modeling approach evaluation plan and operational controls.
• Apply strong design thinking: clarify user needs define decision points design for adoption and make trade-offs explicit.
• Create lightweight high-quality design artifacts (e.g. system context runtime sequence agent/tool map where applicable data lineage decision log) that make build and governance straightforward.
• Make smart design trade-offs: accuracy vs explainability robustness vs speed and model complexity vs operational sustainability.

Build strong ML GenAI and agentic capabilities for actuarial use cases

• Develop models such as predictive risk and behavior models forecasting and scenario models segmentation anomaly detection and optimization approaches.
• Build GenAI capabilities such as retrieval-based solutions structured summarization/extraction and guided analytical workflows to accelerate insight generation.
• Where applicable design agentic workflows that coordinate multiple steps and tools (e.g. retrieval calculations rules and structured outputs) while maintaining traceability and controls.
• Engineer features from large structured and unstructured datasets and ensure solutions remain stable as data and assumptions evolve.

Set a high bar for evaluation and evidence

• Define performance expectations with collaborators and implement out-of-time testing backtesting error analysis stability checks and sensitivity analysis.
• For GenAI and agentic workflows design practical evaluation: scenario coverage edge cases human review rubrics quality scoring and regression testing.
• Document model limitations clearly and build guardrails that ensure outputs are used appropriately.

Partner closely to productionize and operate solutions

• Collaborate with data engineering ML engineering and software teams to productionize: pipelines model packaging CI/CD deployment and monitoring.
• Implement monitoring for data quality drift performance deterioration and operational failures; define remediation actions when thresholds breach.
• Contribute to runbooks and support adoption and UAT with business users.

Work in a governed environment

• Produce documentation and evidence required for model risk review including assumptions validation results monitoring plans and UAT evidence.
• Ensure privacy and security expectations are met through data minimization appropriate access controls and safe handling of sensitive information.

Raise team capability

• Mentor junior scientists through design reviews code reviews and evaluation practices.
• Help standardize how we build solutions using reusable templates checklists and examples to improve consistency and delivery speed.

Required Qualifications:

• 610 years of experience in applied data science machine learning or advanced analytics with demonstrated end-to-end delivery into production beyond notebooks including support for UAT and post-launch iteration.
• Strong Python and SQL with solid software engineering practices: Git-based workflows code reviews unit and integration testing logging readable code structure and basic performance tuning.
• Hands-on experience with modern DS/ML tooling such as scikit-learn PyTorch or TensorFlow and distributed processing platforms such as Spark or Databricks including feature engineering and model development at scale.
• Demonstrated ability to build and communicate solution architecture by producing clear diagrams and short specs. These cover data flow runtime flow interfaces dependencies failure modes and operational controls. Align collaborators on trade-offs and scope.
• Strong evaluation skills across ML and advanced analytics: backtesting or out-of-time testing metric selection error analysis stability testing and sensitivity analysis; ability to translate evaluation into business-ready acceptance criteria.
• Experience building and operating monitored solutions: data quality checks drift detection performance deterioration monitoring alerting and practical remediation approaches.
• Strong communication and collaborator management: ability to explain outputs limitations uncertainty and build decisions in plain language and drive adoption in business workflows with domain partners.
• Actuarial domain depth demonstrated through significant experience partnering with actuarial teams or solving actuarial-context problems with comfort in working with actuarial constraints reconciliation expectations and governed decision processes.
• Working knowledge of GenAI and agentic patterns includes understanding when they add customer value. You should also know how to deploy them responsibly. Experience contributing to a GenAI-enabled capability like retrieval-based solutions structured summarization/extraction or tool-using workflows is required.

Preferred or Nice to have:

• Actuarial background through education credentials including ASA or FSA or progress toward them or substantial experience working in actuarial teams and workflows.
• Experience delivering solutions in governed environments including documentation validation evidence monitoring plans UAT support and approvals.
• Experience with GenAI patterns such as retrieval-based solutions structured outputs tool/function calling and agentic workflows along with practical evaluation methods.
• Familiarity with vector search and embeddings semantic retrieval and orchestration frameworks used to build production GenAI systems.
• Experience implementing GenAI guardrails including accuracy controls safe output formatting data minimization access controls and human review workflows.
• Ability to influence and mentor others through design reviews code reviews and evaluation practices without formal people management responsibility.

When you join our team:

• Well empower you to learn and grow the career you want.
• Well recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team well 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 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

Salary range is expected to be between

If you are applying for this role outside of the primary location please contact for the salary range for your location. 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. 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. If you are applying for this role in the U.S. please contact for more information about U.S.-specific paid time off provisions.