Director, Enterprise Data %26 AI Platforms

About MassDOT:

The 4,000 employees of Massachusetts Department of Transportation (MassDOT) take great pride in connecting the Commonwealth’s residents and communities. MassDOT is responsible for developing, implementing, and coordinating transportation policies and projects for the Commonwealth of Massachusetts and to efficiently plan, design, construct, and maintain a safe statewide transportation system which effectively meets the transportation needs of the Commonwealth. Information about MassDOT’s culture and career opportunities can be found at mass.gov/massdot-careers.

MassDOT’s divisions include Highway, Registry of Motor Vehicles, Aeronautics, and Rail & Transit. Headquarters (Planning & Enterprise Services) provides business and administrative support and policy leadership for each of the four (4) divisions.  

Position Summary:

The Director of Enterprise Data & AI Platforms is a senior leader within the MassDOT Information Technology division, reporting to the Secretariat Chief Information & Technology Officer. This role serves as the technology leader for enterprise data, AI, analytics platforms, and related SAAS platforms.

This leader oversees the end-to-end lifecycle of enterprise AI systems, cloud-based data platforms, and other related Enterprise SAAS Platforms, driving scalable architecture, modern data capabilities, MLOps/LLMOps excellence, responsible AI adoption, and enterprise platform governance across the organization.

The primary work location for this position is 10 Park Plaza, Boston, Massachusetts. The standard work schedule is Monday through Friday, 9:00 AM to 5:00 PM ET. This position follows a hybrid work model, with an expectation of working on-site a minimum of three days per week and remotely on the remaining days, subject to operational business needs.

Core Responsibilities:

Strategy & Value Realization

• Owns the technology strategy, architecture, and delivery of enterprise AI and data platforms, while partnering with business and Chief Data Office (CDO) on use-case prioritization and value realization.
• Identify, prioritize, and scale AI use cases tied to measurable outcomes (operational efficiency, service delivery, customer experience).
• Establish KPIs and maturity models to track the impact and value of AI and data investments.

AI Platform & Engineering Leadership

• Lead the architecture, design, and delivery of scalable AI systems, including GenAI, RAG, and agentic AI solutions.
• Establish and operationalize MLOps/LLMOps frameworks for model lifecycle management, performance, and observability.
• Drive a cloud-first platform strategy, enabling reusable, secure, and scalable AI capabilities across the enterprise.
• Monitor emerging technologies (e.g., cloud services, GPUs, AI tooling) and guide platform evolution.

Data Engineering & Platform Oversight

• Lead development of modern cloud data platforms (data lake, warehouse, real-time pipelines on AWS, Snowflake).
• Ensure availability of AI-ready data through robust data pipelines, integration frameworks, and multimodal data support.
• Oversee ETL/ELT processes, real-time data processing, and data observability practices.
• Establish best practices for data architecture, integration, and platform scalability.

Governance, Risk & Responsible AI

• Build and enforce enterprise Data & AI governance frameworks, including data quality, lineage, privacy, and access controls.
• Establish responsible AI practices ensuring transparency, fairness, security, and regulatory compliance.
• Ensure alignment with EOTSS standards and Commonwealth policies.
• Partner with legal, audit, and security teams to ensure adherence to regulatory and risk requirements.

Operating Model, Adoption & Change Leadership

• Establish and govern an enterprise AI portfolio and delivery model balancing innovation with standardization and control.
• Lead organizational change management efforts to enable adoption of AI solutions at scale.
• Promote AI literacy and workforce development to drive effective and responsible use of AI technologies.
• Enable cross-functional collaboration to embed AI into business processes and decision-making.

Leadership & Cross-Functional Collaboration

• Lead multiple engineering and platform teams responsible for enterprise data, AI, and analytics.
• Partners across IT, business units, data office, security, HR, and operations to co-design and deliver mission-critical solutions.
• Provide executive-level communication and thought leadership on AI and data strategy.
• Support resilience planning, including disaster recovery and continuity of operations for AI and data platforms.

Preferred Qualifications & Experience

• At least 10 years of progressive experience in IT, including data engineering, cloud platforms, and AI/ML delivery, with demonstrated success leading large-scale transformation initiatives.
• Proven senior leadership experience managing large, cross-functional data and AI engineering teams.
• Proven ability to manage enterprise technology portfolios, prioritize AI and data investments, establish performance metrics, and demonstrate measurable business value.
• Demonstrated experience developing and executing enterprise technology strategies, architecture roadmaps, and scalable platform solutions aligned with organizational objectives.
• Strong knowledge of MLOps and LLMOps frameworks, including model deployment, monitoring, performance optimization, and lifecycle management in production environments.
• Demonstrated success translating AI and data capabilities into measurable business outcomes particularly within regulated, complex, or mission-critical environments.
• Exceptional executive communication, stakeholder management, and organizational change leadership skills, with the ability to influence decision-making and drive alignment across diverse business and technical stakeholders.
• Deep expertise in modern enterprise data architectures, cloud platforms, AI/ML technologies, and Software-as-a-Service (SaaS) solutions, including platforms such as AWS, Snowflake, and ServiceNow.
• Strong understanding of enterprise data governance, data privacy and security regulations, and responsible AI principles and frameworks with demonstrated ability to support compliance, risk management, and ethical technology adoption.

Education and Certification(s):

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Engineering, Artificial Intelligence, or a related field preferred, but not required.
• Professional certifications in cloud computing, data engineering, and artificial intelligence, including AWS certifications, Snowflake certifications, and AI/ML-related certifications, are preferred but not required.

A finalist for this position must be able to pass a comprehensive background check including a criminal record check, Department of Revenue (DOR) check, and employment references.