Director, AI

TheDirector Artificial Intelligencewill lead an AI team supporting theLong TermCare (LTC) program in John Hancock and Manulife. This role is accountable for building and scaling AI solutions that improve business processes generate strategic insights and enable measurable impact across the organization.

This is a leadership role that requires a strong combination oftechnical depth business judgment people leadership and delivery excellence. The Director will manage a team ofAI Engineers Data Scientists and technical professionalsresponsible for designing developing deploying andmaintainingproduction-grade AI and machine learning solutions.

The ideal candidate is passionate about AI a continuous learner and someone who actively follows the latest trends inAI GenAI LLMs machine learning data science software engineering and cloud technologies. The candidate should have strong hands-on experience as an individual contributor in AI or data science and be able to guide teams through complex technical decisions. This includes experience across bothtraditional predictive analytics machine learningand MLOpsas well as newer areas such asGenAI LLMs RAG prompt orchestration guardrails LLMOps.

The Director will work closely with business technology risk compliance operations and executive stakeholders toidentifyopportunities shape strategy deliver high-quality AI solutions and communicate impact in clear business terms.

Position Responsibilities:

• Lead the development and delivery of AI ML and GenAI solutions that support theLong TermCare business strategy in John Hancock and Manulife.

• Manage and develop a team of AI Engineers Data Scientists and technical professionals providing coaching technical guidance performance management and career development.

• Own complex AI initiatives from business problem definition through solution design model development engineering deployment adoption and value measurement.

• Partner with business leaders and stakeholders toidentifyhigh-value AI opportunities translate business needs into technical solutions and ensure AI products deliver measurable outcomes.

• Provide technical leadership across traditional data science predictive modeling machine learning GenAI LLMs and production AI engineering.

• Guide the team in building modular scalable reusableAIand GenAI pipelines including model development feature engineering model registries automated retraining and production deployment practices.

• Oversee the deployment of production-grade AI services using modern cloud MLOps DevOps and software engineering practices including containerization CI/CD monitoring observability and model governance.

• Ensure AI solutions are reliable secure scalable cost-effective well-documented and aligned with enterprise architecture security risk and compliance standards.

• Lead the evaluation and adoption of GenAI patterns and tools including LLMs RAG vector search prompt engineering guardrails Azure OpenAI Databricks and internal AI platforms.

• Drive strong engineering and model management practices including testing monitoring model performance tracking drift detection challenger testing and continuous improvement.

• Communicate AI strategy delivery progress risks business value and model impact to senior leaders and cross-functional partners in a clear and practical way.

• Build strong partnerships across business technology data security risk compliance and operations teams to support adoption and long-term success.

• Stay current with advances in AI GenAI data science engineering cloud platforms and emerging technology and bring practical innovation into the teams roadmap.

• Support recruitment onboarding and development of strong AI data science and engineering talent.

Required Qualifications:

• 8 years of experience in AI data science machine learning analytics software engineering or related technical fields.

• 3 years of experience leading or managing technical teams including Data Scientists AI Engineers Machine Learning Engineers or similar roles.

• Strong hands-on background as an individual contributor in AI data science machine learning or AI engineering.

• Proven experience delivering AI or ML solutions from concept to production including business problem framing model development deployment monitoring and value measurement.

• Strong experience with traditional data science and predictive analytics including supervised learning model validation performance measurement and business interpretation of model outputs.

• Strong knowledge of GenAI and LLM-based solution patterns including prompt engineering RAG embeddings vector databases guardrails model evaluation and responsible AI practices.

• Advanced programming experience in Python and SQL.

• Experience with cloud platforms preferably Azure and modern AI/ML platforms such as Azure ML Azure OpenAI Databricks MLflow or similar tools.

• Strong understanding of MLOps DevOps CI/CD testing model monitoring model governance and production support.

• Ability to work with engineering teams on scalable AI architecture APIs data pipelines cloud-native services and production deployment.

• Strong communicationskills with the ability to explain complex AI concepts in simple business language for senior stakeholders.

• Demonstrated ability to influence stakeholders and drive adoption of AI solutions across business and technology teams.

• Advanced degree in Computer Science Data Science Statistics Mathematics Engineering or a related quantitative field preferred; equivalent experience will also be considered.

Preferred Qualifications:

• Experience in insurance financial services healthcare long-term care claims operations.

• Experience leading AI products or platforms in a regulated enterprise environment.

• Strong understanding of responsible AI model risk management data privacy security and compliance expectations.

• Experience with large-scale data environments including Databricks Spark Delta Lake relational databases and cloud data platforms.

• Experience with production engineering practices such as Docker Kubernetes APIs infrastructure-as-code logging tracing monitoring and alerting.

• Strong consulting and stakeholder management skills with the ability tooperateeffectively across business and technology teams.

• Demonstrated ability to build high-performing inclusive and collaborative teams.

• Active learner with a strong external network anda track recordof staying current with AI GenAI engineering and technology trends.

Ideal Candidate Profile

The ideal candidate is a hands-on AI leader who canoperateat both thestrategy leveland thetechnical execution level. This person can engage senior business leaders on priorities and value while also guiding AI Engineers and Data Scientists on architecture modeling choices engineering standards and production delivery.

This candidate should bring:

• Deep curiosity and passion for AI and emerging technology.

• Strong technical credibility with AI Engineers and Data Scientists.

• Practical experience delivering AI solutions in production.

• A strong understanding of both traditional ML and modern GenAI.

• Clear communication and strong executive presence.

• A collaborative leadership style focused on coaching accountability and measurable impact.

When you join our team:

• Wellempower you to learn and grow the career you want.

• Wellrecognize and support you in a flexible environment where well-being and inclusion are more than just words.

• As part of our global teamwellsupport you in shaping the future you want to see.

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