Job Type
Full-time
Description
The Director Technology and Innovation reports to the Chief Information Officer and is responsible for advancing the firm's use of emerging technology, data, analytics, automation, and artificial intelligence. The Director partners with business, practice, and technology leaders to translate needs into a prioritized portfolio of practical, scalable solutions that improve project delivery, operational performance, employee experience, and client value. This role guides initiatives from discovery and business-case development through pilot, implementation, adoption, governance, and value measurement. The Director also helps strengthen the firm's data and AI capabilities by coordinating internal resources, external partners, standards, and responsible-use practices.
Technology Advancement Strategy and Roadmap - Develop and maintain a technology advancement roadmap aligned with business priorities, practice needs, client expectations, and the CIO's technology direction.
- Identify and assess emerging technologies and use cases based on business value, feasibility, risk, scalability, and organizational readiness.
- Prepare business cases, recommendations, success measures, and portfolio updates for review by the CIO and other decision-makers.
- Monitor AEC and broader technology trends and recommend focused opportunities for evaluation or investment.
Data, AI, and Digital Innovation - Provide program leadership for data, analytics, automation, machine learning, generative AI, and related digital initiatives in partnership with technical and business stakeholders.
- Coordinate with data, security, infrastructure, application, and architecture resources to define solution requirements and delivery plans.
- Guide initiatives from discovery and proof of concept through pilot, deployment, operational handoff, measurement, and continuous improvement.
- Promote reusable, supportable solutions that align with the firm's enterprise architecture and technology standards.
Practice Enablement - Build relationships with architecture, engineering, planning, project management, and market leaders to understand workflow challenges and technology opportunities.
- Translate practice needs into clear product, data, integration, adoption, and change-management requirements.
- Advance practical use cases such as knowledge and project archive search, pre-design analysis, code and compliance research, product and material intelligence, project-status reporting, drawing and specification support, and administrative automation.
- Ensure proposed solutions support professional judgment, quality standards, contractual commitments, client requirements, and risk-management practices.
Portfolio, Adoption, and Value Realization - Manage a structured intake and prioritization process for technology, data, and AI opportunities.
- Coordinate initiative plans, dependencies, risks, budgets, resources, adoption activities, and measures of success.
- Partner with business owners to define expected outcomes, monitor adoption and performance, and document realized value.
- Provide clear progress reporting and recommendations to the CIO, sponsors, and governance groups.
Governance, Risk, and Responsible AI - Partner with Information Technology, Legal, and business stakeholders to implement governance for emerging technology, data, and AI.
- Help establish and apply standards for data quality, ownership, stewardship, access, retention, privacy, model oversight, acceptable use, and human review.
- Coordinate governance for employee-enabled AI tools, including evaluation, procurement, access, integration, data use, security, and ongoing oversight.
- Support protection of firm intellectual property, project information, client information, and institutional knowledge.
Organizational and Team Leadership - Build, lead, and develop a high-performing Data and AI team spanning data engineering, AI/MLOps, AEC solutions, product management, architecture, data science, and governance.
- Determine the appropriate mix of employees, external specialists, vendors, and implementation partners; recruit specialized talent and upskill internal colleagues.
- Establish goals, delivery expectations, operating rhythms, and measures for the function and ensure external knowledge is documented and retained.
- Promote data literacy, responsible AI fluency, collaboration, experimentation, accountability, and disciplined execution across the firm.
Stakeholder, Financial and Vendor Management - Build strong partnerships with practice leaders, project teams, Finance, Operations, corporate functions, clients, and external technology partners.
- Facilitate decisions related to investments, portfolio priorities, data ownership, platform standards, governance, and adoption.
- Lead vendor evaluation and management, including expectations for performance, security, scalability, service quality, knowledge transfer, and business value.
- Manage budgets and communicate the cost, benefit, risk, and return associated with the data and AI portfolio.
- Build and maintain relationships across the company to foster trust and accountability.
Other Duties - Perform other related duties as assigned.
Requirements
- Bachelor's degree in data science, computer science, information systems, engineering, architecture, construction technology, business, or a related field.
- Progressive experience in technology advancement, data, artificial intelligence, analytics, digital transformation, product management, or a closely related function, including experience leading complex cross-functional initiatives.
- Demonstrated experience developing roadmaps, business cases, implementation plans, governance practices, and measures of success for technology initiatives.
- Experience coordinating multidisciplinary teams, consultants, vendors, implementation partners, budgets, and organizational change.
- Working knowledge of enterprise data environments, analytics, automation, AI solutions, systems integration, security, privacy, and responsible technology use.
- Strong communication, facilitation, stakeholder-management, problem-solving, and change-management skills.
- An equivalent combination of education and experience may be considered in lieu of the requirements listed.
Preferred Education & Experience - Advanced degree in a technology, design, engineering, architecture, or business discipline.
- Experience in the architecture, engineering, and construction industry, with an understanding of AEC project delivery, professional practice, technology platforms, and business processes.
- Familiarity with BIM, GIS, design technology, project information management, specifications, visualization, digital delivery, ERP, and AEC project-management workflows.
- Experience with cloud data platforms, data lakehouse environments, semantic models, generative AI, agentic workflows, machine learning operations, or intelligent automation.
- Experience integrating emerging technology with enterprise and AEC platforms.
- Familiarity with professional-services measures such as utilization, project performance, labor efficiency, backlog, revenue, margin, and return on investment.
- Experience supporting a technology innovation portfolio, data office, AI program, digital practice function, or center of excellence.
- Relevant technical, cloud, data, AI, architecture, engineering, product, change-management, or project-management credentials.
Desired Knowledge, Skills, Abilities & Behaviors - Ability to translate business and AEC practice needs into clear technology priorities and executable plans.
- Strategic thinking paired with practical, disciplined execution.
- Working knowledge of emerging technology, enterprise data, analytics, automation, and AI trends affecting the AEC industry.
- Business and financial acumen, including evaluation of value, cost, feasibility, risk, and scalability.
- Program and portfolio management skills, with accountability for scope, resources, dependencies, adoption, and outcomes.
- Change leadership that builds trust, capability, adoption, and responsible experimentation.
- Ability to influence and align practice, Technology, Finance, Operations, Legal, Security, and executive stakeholders without relying solely on formal authority.
- Effective team, partner, and vendor leadership, including knowledge-transfer and documentation expectations.
- Clear communication of complex technical concepts in practical business language.
- Commitment to professional judgment, security, governance, privacy, and client and firm confidentiality.
Physical Demands: - ??Prolonged sitting?
- Travel requirements: Occasional, based on business need.
Work Environment: - ??Standard office environment?
