Director of AI Strategy & Adoption

Job Description

Job Description

Hazen is hiring a Director of AI Strategy & Adoption to make AI a routine part of how we design, deliver and run water projects. You will build and lead a team that works with scientists and engineers to develop strategic AI solutions for some of the most challenging problems in the water industry.

Hazen and Sawyer is a privately held, employee-owned engineering firm of roughly 2,500 people, focused exclusively on the water industry. Our work is technical, regulated and high-stakes, so AI here has to be accurate, defensible and useful to licensed engineers, not just impressive in a demo.

This is a senior leadership role. You will work with management to develop the direction for AI across the firm, build and lead the team and governance around it, and turn pilots into daily practice for thousands of people across technical practices, project delivery and corporate functions.

Work Setting:  In-office position with a hybrid schedule and periodic travel to other offices and client sites.

Why Hazen and Sawyer:

• Founded in 1951 by the son of Allen Hazen (developer of the Hazen-Williams equation), we are an employee-owned company with a singular focus on "all things water."
• Our work includes planning, design, and oversight of construction of environmental infrastructure – for water, wastewater, and stormwater management.
• We foster a work environment that encourages creativity and professional development by minimizing bureaucracy.
• We recruit talented professionals, provide them with challenging, interesting, and creative assignments, and furnish them with the tools they need to succeed.
• We currently have over 2,000 employees in 70+ offices throughout the United States, Latin America, Canada, and the UK.  

Key Responsibilities:

• Develop Hazen's multi-year AI vision and roadmap, tied to firm strategy, client value and employee-ownership goals. This will require coordinating across groups and soliciting input from technical and business user groups and the Board.
• Prioritize use cases by value, risk and effort, and make recommendations as to what to build, buy or partner on.
• Track the fast-moving AI landscape and brief executives and the Board on what matters for Hazen. This includes tracking and reporting on developments in the: legal, procurement, ethical and public acceptance realms.

Adoption and change management

• Lead firm-wide adoption of AI tools, with practice-level champions, training, and clear guidance on when and how to use them. Collaborate with Communications to develop relevant campaigns
• Work with practice leaders, corporate service directors and project managers to embed AI in proposals, design, QA/QC, reporting and project controls.
• Gather feedback and real examples from practitioners, and act on what you learn.

Implementation and platforms

• Direct the selection, configuration and further rollout of enterprise AI platforms (such as Microsoft Copilot and Claude) and the integrations that connect them to Hazen's data and systems, partnering with Legal and IT to ensure AI tools access only data and systems they are permitted to use.
• Partner with IT, cybersecurity and enterprise software teams on architecture, identity, data access and cost management.
• Oversee custom AI solutions and agents for engineering and business workflows, from prototype to supported production service.

Governance, risk and responsible use

• Recommend refinements to AI policy, and develop an approved-use framework and an intake process for new tools and use cases.
• Identify and escalate AI-related confidentiality, client data, intellectual property, professional liability and contractualrisks, in partnership with Legal, Risk and the Director of Information Technology.
• Set standards for human review of AI output, so licensed engineers remain accountable for sealed work.

Team and partners

• Build and lead a small, high-caliber AI team, and extend it through vendors, academia and industry peers.
• Represent Hazen externally on AI with clients, regulators and professional bodies.

Required Qualifications:

• Bachelor's degree in engineering, computer science, data science or a related field; advanced degree preferred.
• 10+ years of experience in technology, data or digital leadership, including leading enterprise AI or machine learning programs from strategy through deployment.
• A record of driving adoption at scale: you have changed how a large, professional workforce works, not only built tools.
• Working knowledge of generative AI, large language models, agents, retrieval and evaluation methods, and enterprise AI platforms.
• Experience with AI governance, data security and responsible-use frameworks in a regulated or professional-services setting, including data access controls and client data restrictions.
• Strong executive communication: you can explain trade-offs to the Board and to a skeptical senior engineer in the same day.
• Experience hiring, leading and developing technical teams.

Preferred Qualifications:

• Background in engineering, architecture or other professional services.
• Deep familiarity with engineering practice and professional liability.
• Experience with Microsoft 365 and Azure, and with BIM, GIS or hydraulic and process modeling tools.
• Familiarity with the economics of an employee-owned or partnership-style firm.
• Experience integrating AI with data platforms, document-heavy workflows and project controls systems.

What We Offer:

• Comprehensive health benefits (medical, dental, vision, and prescription plans)
• Pre-tax flexible spending plans for medical, dependent care, and transportation
• Short and long-term disability, and employer paid life insurance
• Paid holidays, floating holidays, and paid time off (PTO)
• Employer-contributed 401(k) plan and additional financial planning support
• Professional growth opportunities, including tuition reimbursement, in-house training, and incentives for professional registration and professional organization memberships
• Starting pay range for this position depends on skills, experience, education and geographical location

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