Director, AI

Manulife • Boston, MA

1d • Hybrid

About The Position

The Director, Artificial Intelligence will lead an AI team supporting the Long Term Care program at John Hancock and Manulife. The role is accountable for building and scaling AI solutions that improve business processes, generate strategic insights, and deliver measurable organizational impact. The Director manages AI Engineers, Data Scientists, and other technical professionals responsible for designing, developing, deploying, and maintaining production-grade AI and machine learning solutions. This leadership position combines technical depth, business judgment, people leadership, and delivery excellence, and calls for hands-on experience in AI or data science alongside the ability to guide teams through complex technical decisions.

The Director will lead work across traditional predictive analytics, machine learning, and MLOps, as well as GenAI, LLMs, RAG, prompt orchestration, guardrails, and LLMOps. They will collaborate with business, technology, risk, compliance, operations, and executive stakeholders to identify opportunities, shape strategy, deliver high-quality solutions, and communicate impact in business terms. The role oversees the full lifecycle of AI initiatives, from problem definition through design, development, deployment, adoption, and value measurement, while ensuring solutions meet enterprise architecture, security, risk, and compliance standards.

The ideal candidate is a hands-on AI leader able to work at both strategic and technical execution levels: engaging senior leaders on priorities and value while guiding technical teams on architecture, modeling, engineering standards, and production delivery. The position is based in Boston, Massachusetts, with a hybrid working arrangement. The role is an existing vacancy.

Requirements

• At least 8 years of experience in AI, data science, machine learning, analytics, software engineering, or related technical fields.
• At least 3 years of experience leading or managing technical teams, including Data Scientists, AI Engineers, Machine Learning Engineers, or similar roles.
• Strong hands-on individual-contributor background 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 communication skills and ability to explain complex AI concepts in simple business language to 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 is also considered.

Nice To Haves

• Experience in insurance, financial services, healthcare, long-term care, claims, or 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 to operate effectively across business and technology teams.
• Demonstrated ability to build high-performing, inclusive, and collaborative teams.
• Active learner with a strong external network and a record of staying current with AI, GenAI, engineering, and technology trends.

Responsibilities

• Lead development and delivery of AI, ML, and GenAI solutions supporting the Long Term Care business strategy at John Hancock and Manulife.
• Manage, coach, and develop AI Engineers, Data Scientists, and other technical professionals, including providing 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 to identify high-value AI opportunities, translate business needs into technical solutions, and ensure measurable outcomes.
• Provide technical leadership across traditional data science, predictive modeling, machine learning, GenAI, LLMs, and production AI engineering.
• Guide development of modular, scalable, reusable AI and GenAI pipelines, including model development, feature engineering, model registries, automated retraining, and production deployment practices.
• Oversee deployment of production-grade AI services using 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 evaluation and adoption of GenAI patterns and tools, including LLMs, RAG, vector search, prompt engineering, guardrails, Azure OpenAI, Databricks, and internal AI platforms.
• Drive 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 clearly to senior leaders and cross-functional partners.
• Build partnerships across business, technology, data, security, risk, compliance, and operations 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 team roadmap.
• Support recruitment, onboarding, and development of AI, data science, and engineering talent.

Benefits

• Customizable health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage.
• Adoption/surrogacy and wellness benefits.
• Employee and family assistance plans.
• Retirement savings plans, including pension/401(k) savings plans and a global share ownership plan with employer matching contributions.
• Financial education and counseling resources.
• Up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year in the U.S.
• Statutory leaves of absence.
• Incentive programs and incentive compensation tied to business and individual performance.
• Flexible working environment; the posting also highlights well-being and inclusion.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed