Senior Applied AI Engineer - GenAI Systems (Toronto)

Senior Applied AI Engineer – GenAI Systems (Toronto)

Manulifes Group Functions AI team is scaling AI and advanced analytics capabilities across Finance, Treasury, Actuarial, and related enterprise functions to improve decision-making and insight generation.

Responsibilities

• Work closely with business stakeholders and engineering partners to deliver explainable, robust, and operationally sustainable solutions that accelerate decision cycles and improve consistency.
• Own end-to-end solution design for actuarial AI; translate business problems into clear solution approaches including workflow, data flow, modeling, evaluation, 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, data lineage, decision log) to simplify build and governance.
• Make smart design trade‑offs among accuracy vs explainability, robustness vs speed, and model complexity vs operational sustainability.
• Build strong ML, GenAI, and agentic capabilities for actuarial use cases; develop predictive risk and behavior models, forecasting, scenario models, segmentation, anomaly detection, and optimization approaches.
• Develop GenAI capabilities such as retrieval‑based solutions, structured summarization/extraction, and guided analytical workflows; design agentic workflows coordinating multiple steps and tools 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, 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 to ensure appropriate use of outputs.
• 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.
• 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.
• Mentor junior scientists through design reviews, code reviews, and evaluation practices; help standardize solution building using reusable templates, checklists, and examples.

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, TensorFlow, or related libraries.
• Experience with distributed processing platforms such as Spark or Databricks, including feature engineering and model development at scale.
• Demonstrated ability to design and communicate solution architecture: produce clear diagrams and short specs covering data flow, runtime flow, interfaces, dependencies, failure modes, and operational controls; align stakeholders 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 stakeholder management: ability to explain outputs, limitations, uncertainty, and design decisions in plain language, and drive adoption in business workflows with domain partners.
• Working knowledge of GenAI and agentic patterns, including when they add value and how to deploy them responsibly; experience contributing to at least one GenAI‑enabled capability such as retrieval‑based solutions, structured summarization/extraction, or tool‑using workflows.

Preferred Qualifications

• 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.

Benefits

Employees offer 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, employee/family assistance plans. We also offer various retirement savings plans and financial education resources. Our paid time off program includes holidays, vacation, personal, and sick days, plus statutory leaves of absence.

Equal Opportunity Employer

Manulife is an Equal Opportunity Employer. We embrace 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.