Director, AI Platform & Governance

Posted 10 Days Ago
Be an Early Applicant
Hiring Remotely in Hong Kong
Remote
Expert/Leader
Fintech • Insurance • Financial Services
The Role
Leads the enterprise AI platform strategy, architecture, delivery, operations, and roadmap. Oversees AI platform capabilities including LLMs, RAG, agents, model registries, observability, and orchestration. Establishes AI governance, responsible AI, MLOps, LLMOps, security, risk, compliance, and lifecycle controls. Leads a multidisciplinary technical squad, drives scalable and secure platform engineering, and partners with executives, technology, data, legal, risk, compliance, and security teams to deliver enterprise AI capabilities.
Summary Generated by Built In

Director, AI Platform & Governance


Position Responsibilities:


1. AI Platform Strategy & Roadmap


  • Own the enterprise AI Platform strategy, roadmap, and target-state architecture.
  • Define and evolve the organization’s AI capabilities, standards, and operating model.
  • Establish platform capabilities that enable rapid, secure, and reusable AI solution development across business domains.
  • Partner with business, Technology, and Data leaders to understand current and future AI requirements.
  • Develop a multi-year roadmap covering AI infrastructure, platform capabilities, governance controls, developer experience, and operational excellence.
  • Evaluate emerging AI technologies and define adoption strategies aligned with enterprise objectives.

2. AI Platform Ownership


  • Own the design, delivery, operation, and continuous enhancement of the enterprise AI Platform.
  • Lead implementation of core AI Platform capabilities, including:
  • AI Gateway
  • LLM Platform
  • Prompt Management
  • Agentic AI Framework
  • Knowledge Retrieval and RAG Services
  • Model Registry
  • Vector Databases
  • AI Workflow Orchestration
  • Model Monitoring and Observability
  • Cost and Usage Management
  • AI Development Tooling
  • Establish reusable platform services that minimize duplication across use cases and business domains.
  • Drive platform reliability, scalability, resilience, and performance.
  • Ensure AI platform services meet enterprise availability and operational requirements.

3. AI Governance & Responsible AI


  • Establish and maintain enterprise AI governance frameworks aligned with regulatory requirements and internal policies.
  • Lead implementation of governance controls throughout the AI lifecycle.
  • Ensure AI systems are developed, deployed, monitored, and retired in accordance with enterprise standards.
  • Define model registration, approval, monitoring, validation, and review processes.
  • Establish responsible AI controls covering fairness, transparency, explainability, accountability, and human oversight.
  • Partner with Risk, Compliance, Legal, and Internal Audit to ensure AI governance requirements are effectively embedded within platform processes.
  • Support regulatory examinations, audits, model reviews, and governance reporting.

4. MLOps, LLMOps & AI Operations


  • Establish enterprise MLOps and LLMOps capabilities.
  • Define standards and tooling for model deployment, testing, versioning, monitoring, rollback, and lifecycle management.
  • Implement automated pipelines supporting AI development and deployment.
  • Establish model performance monitoring and drift detection frameworks.
  • Define operational processes for incident management, service recovery, and platform support.
  • Drive observability across AI systems, models, prompts, agents, and infrastructure components.
  • Ensure platform utilization, cost efficiency, and resource optimization.

5. Security, Risk & Compliance


  • Partner with Information Security and Enterprise Architecture teams to establish secure AI architectures.
  • Implement controls for access management, data protection, secret management, model access, and API security.
  • Ensure compliance with enterprise security standards and regulatory obligations.
  • Establish risk assessment and approval processes for AI solutions.
  • Define technical guardrails to prevent misuse, data leakage, unsafe outputs, and policy violations.
  • Support threat modelling and security reviews for AI systems and infrastructure.

6. Technical Architecture & Engineering Leadership


  • Provide technical leadership and architectural direction across AI technologies.
  • Establish standards for:
    • Generative AI
    • AI Agents
    • Machine Learning Platforms
    • Prompt Engineering
    • RAG Architectures
    • Knowledge Management
    • AI APIs and Integrations
    • Cloud-native AI Services
  • Review solution architectures and provide guidance to delivery squads.
  • Promote engineering best practices, reusable patterns, and platform-first thinking.
  • Partner with Enterprise Architecture to ensure alignment with broader technology strategy.

7. Squad Leadership


  • Lead the AI Platform & Governance Squad comprising AI engineers, platform engineers, MLOps engineers, and governance specialists.
  • Establish squad objectives, priorities, delivery plans, and performance measures.
  • Drive execution against platform and governance roadmaps.
  • Foster close collaboration with business domain squads, Data teams, Technology teams, Risk, Compliance, and Security stakeholders.
  • Promote a culture of engineering excellence, reliability, automation, continuous learning, and operational discipline.
  • Develop technical capabilities within the squad and create a high-performing engineering environment.
  • Build strong engineering practices across AI development, deployment, monitoring, and governance.

Required Qualifications:


  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or a related discipline.
  • Master's degree preferred.
  • 10+ years of experience in AI, machine learning, software engineering, platform engineering, cloud engineering, or related fields.
  • 5+ years of experience leading technical teams, platforms, or engineering organizations.
  • Proven experience building and operating enterprise-scale AI, machine learning, or cloud platforms.
  • Experience leading enterprise architecture, platform engineering, MLOps, LLMOps, or AI infrastructure initiatives.
  • Experience implementing AI governance and model risk management processes within regulated industries.
  • Financial services or insurance experience strongly preferred.
  • Deep understanding of Generative AI, large language models, AI agents, and modern AI architectures.
  • Strong knowledge of AI Platform technologies and patterns, including:
    • MLOps
    • LLMOps
    • RAG
    • Vector Databases
    • AI Gateways
    • AI Agent Frameworks
    • Model Registries
    • Observability Platforms
  • Strong cloud architecture knowledge across Azure, AWS, Alibaba Cloud, or equivalent environments.
  • Experience with containerization, Kubernetes, API management, and modern DevSecOps practices.
  • Experience designing scalable, secure, and highly available enterprise platforms.
  • Strong understanding of AI security, privacy, and governance requirements.
  • Hands-on experience with Python and modern AI engineering frameworks.
  • Strategic technology leadership.
  • Strong architecture and systems thinking.
  • Excellent stakeholder management and influencing skills.
  • Ability to communicate complex technical concepts to executive audiences.
  • Strong execution focus with a demonstrated ability to deliver enterprise platforms at scale.
  • Ability to balance technology advancement, governance, security, and operational excellence.
  • Strong problem-solving and decision-making capability.
  • Passion for building enterprise AI capabilities that enable business transformation.

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 https://www.manulife.com/en/about/our-story.html.

Manulife 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 [email protected].

Working Arrangement

Hybrid

Skills Required

  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or a related discipline
  • 10+ years of experience in AI, machine learning, software engineering, platform engineering, cloud engineering, or related fields
  • 5+ years of experience leading technical teams, platforms, or engineering organizations
  • Experience building and operating enterprise-scale AI, machine learning, or cloud platforms
  • Experience leading enterprise architecture, platform engineering, MLOps, LLMOps, or AI infrastructure initiatives
  • Experience implementing AI governance and model risk management processes within regulated industries
  • Deep understanding of Generative AI, large language models, AI agents, and modern AI architectures
  • Strong knowledge of MLOps, LLMOps, RAG, vector databases, AI gateways, AI agent frameworks, model registries, and observability platforms
  • Strong cloud architecture knowledge across Azure, AWS, Alibaba Cloud, or equivalent environments
  • Experience with containerization, Kubernetes, API management, and modern DevSecOps practices
  • Experience designing scalable, secure, and highly available enterprise platforms
  • Strong understanding of AI security, privacy, and governance requirements
  • Hands-on experience with Python and modern AI engineering frameworks
  • Strategic technology leadership and strong architecture and systems thinking
  • Excellent stakeholder management, influencing, and executive communication skills
  • Ability to deliver enterprise platforms at scale and balance technology advancement, governance, security, and operational excellence
  • Strong problem-solving and decision-making capability
  • Master's degree
  • Financial services or insurance experience

Manulife Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Manulife and has not been reviewed or approved by Manulife.

  • Healthcare Strength — Healthcare coverage is portrayed as comprehensive, spanning medical, dental, prescription drugs, vision, critical illness, and short- and long-term disability. Mental-health support is emphasized via EAP-style services and high annual coverage limits in some regions, alongside wellness programs and navigation tools.
  • Retirement Support — Retirement offerings are positioned as a meaningful part of total rewards, including group RRSP/defined contribution pension options and employer matching in some cases. Ownership-related programs such as share purchase/stock options are also described as available for eligible employees.
  • Flexible Benefits — Benefits are described as robust and flexible, with customizable packages and spending-account style options in some plans. Digital tools (mobile app/claims) and reward-linked wellness programs are framed as making benefits easier to use and more engaging.

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The Company
HQ: Toronto, Ontario
32,427 Employees
Year Founded: 1887

What We Do

Manulife is a leading international financial services group that helps people make their decisions easier and lives better. With our global headquarters in Toronto, we operate as Manulife across our offices in Canada, Asia, and Europe, and primarily as John Hancock in the United States. We have more than 40,000 employees, over 116,000 agents serving ~34 million customers worldwide, and over $1.3 trillion in assets under management and administration. Visit www.Manulife.com to find out more. For Manulife terms of use, please visit http://bit.ly/SM_Terms

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