Director, AI

Manulife

. Lead development and delivery of AI, ML, and GenAI solutions supporting the Long Term Care business strategy in John Hancock and Manulife .

Posted 10/26/2026full-timeBoston • Massachusetts • United StatesLead💰 $127,330 - $236,470 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI and ML solution development, managing technical teams, and delivering scalable, production-grade AI services. Proficient in translating business needs into technical solutions while ensuring compliance and reliability across AI initiatives.

Highest-signal resume keywords

AI Solution DevelopmentTeam LeadershipMLOps and DevOpsCloud Platforms (Azure)Predictive Analytics

ATS Keywords

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Hard Skills

AI EngineeringMachine LearningData SciencePython ProgrammingSQL ProgrammingGenAI KnowledgePredictive ModelingModel EvaluationPrompt EngineeringData Privacy

Soft Skills

Strong CommunicationStakeholder InfluenceCoaching and Mentoring

Tools & Technologies

Azure MLAzure OpenAIDatabricksMLflowDockerKubernetesAPIsInfrastructure-as-CodeMonitoring ToolsLogging Tools

Industry Keywords

InsuranceFinancial ServicesHealthcareLong-Term CareModel Risk ManagementComplianceData GovernanceCloud Data PlatformsLarge-Scale Data EnvironmentsRelational Databases

Tech Stack

Tools & technologies

AzureCloudDockerKubernetesPythonSparkSQL

About the role

Key responsibilities & impact

Lead development and delivery of AI, ML, and GenAI solutions supporting the Long Term Care business strategy in John Hancock and Manulife
Manage and develop AI Engineers, Data Scientists, and technical professionals through 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 to identify high-value AI opportunities and translate business needs into technical solutions
Provide technical leadership across predictive modeling, machine learning, GenAI, LLMs, and production AI engineering
Guide development of modular, scalable, reusable AI and GenAI pipelines
Oversee production-grade AI services using cloud, MLOps, DevOps, and software engineering practices
Ensure solutions are reliable, secure, scalable, cost-effective, documented, and compliant with enterprise standards
Lead evaluation and adoption of LLMs, RAG, vector search, prompt engineering, guardrails, Azure OpenAI, Databricks, and internal AI platforms
Drive 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
Build partnerships across business, technology, data, security, risk, compliance, and operations teams
Stay current with AI, GenAI, data science, engineering, cloud platforms, and emerging technologies
Support recruitment, onboarding, and development of AI, data science, and engineering talent

Requirements

What you’ll need

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
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
Strong experience with traditional data science and predictive analytics
Strong knowledge of GenAI and LLM-based solution patterns, including prompt engineering, RAG, embeddings, vector databases, guardrails, model evaluation, and responsible AI
Advanced programming experience in Python and SQL
Experience with cloud platforms, preferably Azure, and AI/ML platforms such as Azure ML, Azure OpenAI, Databricks, and MLflow
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 for explaining complex AI concepts in business language
Ability to influence stakeholders and drive AI adoption
Advanced degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field preferred; equivalent experience considered
Preferred: experience in insurance, financial services, healthcare, long-term care, claims, or operations
Preferred: experience leading AI products or platforms in a regulated enterprise
Preferred: responsible AI, model risk management, data privacy, security, and compliance knowledge
Preferred: large-scale data environments including Databricks, Spark, Delta Lake, relational databases, and cloud data platforms
Preferred: Docker, Kubernetes, APIs, infrastructure-as-code, logging, tracing, monitoring, and alerting experience

Benefits

Comp & perks

Flexible work environment supporting well-being and inclusion
Learning and career growth support
Health insurance
Dental insurance
Mental health benefits
Vision insurance
Short- and long-term disability insurance
Life and AD&D insurance
Adoption/surrogacy benefits
Wellness benefits
Employee/family assistance plans
Retirement savings plans, including pension and 401(k)
Global share ownership plan with employer matching contributions
Financial education and counseling resources
Up to 11 paid holidays in the U.S. each year
3 personal days in the U.S. each year
150 hours of vacation in the U.S. each year
40 hours of sick time in the U.S. each year, or more where required by law
Statutory leaves of absence
Incentive programs and incentive compensation tied to business and individual performance