Director of Product, AI, Machine Learning & Data Engineering

If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
 

Pay Range: $185,500.00 - $333,900.00

Job Description

Are you ready to revolutionize how education is delivered and experienced? As the Director of Product for AI, ML, and Data Engineering at WGU, you’ll spearhead cutting-edge, data-driven solutions that redefine success for both students and staff. From crafting personalized learning experiences to leveraging predictive analytics, you’ll play a pivotal role in shaping the strategic vision for AI and data innovation in higher education.

This isn’t just about building products—it’s about driving impact. You’ll collaborate with diverse stakeholders, lead high-performing teams, and create scalable, transformative technologies that align with WGU’s mission to unlock equitable, efficient, and effective education for all.

Join us on this exciting journey to create the tools and platforms that will define the next generation of learning. Let’s build a smarter, more inclusive future together!

Key Responsibilities:

• Product Leadership & Strategy: Define the strategic vision and roadmap for data engineering, ML, and AI solutions, aligning with institutional goals.

• Ownership Scope: Enterprise Rules Platform and Center of Excellence, Data Governance, Data Architecture and Lifecycle Management, Support for AI Governance.

• Stakeholder Collaboration: Coordinate with key stakeholders and leadership on product prioritization, quality, and timeline expectations.

• Product Development: Lead the development and successful launch of innovative products and services for student- and staff-facing solutions.

• Team Support: Effectively support product managers and analysts to execute on the vision and roadmaps for WGU products.

• Vendor & Relationship Management: Maintain and build strong relationships with business owners, stakeholders, team members, and key vendors.

• Software Oversight: Oversee the selection and sourcing of WGU software to ensure high-quality, scalable tools and platforms.

• Data-Driven Decision Making: Monitor KPIs and direct effective action to promote successful business outcomes.

• Customer-Centric Strategy: Utilize customer feedback and competitive data to inform business strategies and product enhancements.

Qualifications:

• Extensive experience in product leadership within data engineering, AI, and/or ML.

• Experience desired in Enterprise Rules, Centers of Excellence, Data Governance, Data Architecture, and Lifecycle Management, as well as support for AI Governance.

• Strong technical expertise in data architectures, cloud technologies, and ML frameworks.

• Proven success in managing complex product portfolios and high-performing teams.

• Exceptional skills in stakeholder collaboration, communication, and strategic planning.

Key Duties

Strategic Leadership and Vision:

• Develop and implement a strategic vision for AI, machine learning, and data engineering solutions that support digital transformation in higher education.

• Align product strategies with WGU goals, such as student success, retention, operational efficiency, and research excellence.

Product Portfolio Management:

• Oversee the development and lifecycle of smart automation (e.g. AI, ML, Rules) and data-centric products tailored for higher education use cases, such as personalized learning platforms, predictive analytics for student retention, and institutional data management tools.

• Oversee the selection of third-party technologies that can accelerate achieving our business objectives while aligning with our desire to own our intellectual property and preserve our institutional objectives.

• Ensure alignment of product initiatives with institutional accreditation, regulatory requirements, diversity, equity, inclusion (DEI) principles, and WGU goals.

Team Leadership and Development:

• Lead and mentor a cross-functional Product Management team specializing in AI, ML, and data solutions for WGU business objectives.

• Cultivate a culture of collaboration, ethical AI and student data use, and continuous professional development within the team.

Technical Strategy and Collaboration:

• Collaborate closely with architecture, engineering, data science, and institutional research teams to build solutions that enhance student outcomes, faculty effectiveness, and administrative decision-making.

• Ensure alignment with enterprise IT infrastructure, Databricks, LMS, student records, and all other data systems of record.

• Create a center of excellence around the WGU vision for data and analytics that shape our success.

Product Roadmap and Prioritization:

• Develop product roadmaps focused on improving student success metrics, faculty research capabilities, and institutional efficiency.

• Use objective prioritization frameworks tailored to the education sector, balancing student impact, compliance, and technological feasibility.

Stakeholder Management and Communication:

• Serve as a lead liaison between product teams and key institutional stakeholders, including deans, provosts, CIOs, and faculty committees.

• Effectively communicate product strategies and outcomes to leadership while ensuring transparency around AI and data ethics in educational settings.

Customer-Centric Innovation:

• Drive a student- and faculty-first approach by aligning intelligent automation tools with real educational challenges such as personalized learning, academic advising, and early intervention for at-risk students.

• Implement user research strategies that engage diverse groups of students and educators in the co-design of products.

Data Governance and Ethical AI Practices:

• Lead data governance efforts to ensure compliance with FERPA, GDPR, and other education-focused data privacy regulations.

• Advocate for transparent, explainable, and bias-aware AI models that support equitable educational outcomes.

Business Outcomes and Impact:

• Define and measure success metrics aligned with higher education priorities, such as increased retention rates, improved learning outcomes, and enhanced operational efficiency.

• Track the impact of AI-driven interventions on student success and institutional performance using rigorous, evidence-based methodologies.

Partnerships and Ecosystem Management:

• Foster strategic collaborations with EdTech vendors, research institutions, and consortia.

• Explore partnerships for joint development of open-source AI tools and frameworks that benefit the broader higher education community.

Background Elements for Success

Education:

• Master’s degree or Ph.D. in Computer Science, Data Science, AI, Machine Learning, or a related technical field.

• Additional education or certifications in product management, educational technology, or leadership are preferred.

Experience:

• 12+ years of experience in technical product management, data engineering, or AI leadership roles, with at least 5 years in a senior leadership capacity.

• Proven track record of delivering data-driven, AI/ML-driven products in the higher education sector or closely related domains.

• Experience leading cross-functional teams across data science, engineering, and product management.

• Familiarity with the data architecture inherent in higher education domains, including the use of data warehousing and related data platforms.

Technical Expertise:

• Strong understanding of machine learning pipelines, data engineering frameworks, and cloud platforms.

• Hands-on knowledge of AI models and Business Rules relevant to education, such as personalized learning algorithms and predictive analytics for student success.

• Experience with data governance and privacy frameworks, including FERPA and GDPR compliance.

Leadership and Strategic Skills:

• Demonstrated success in strategic planning and managing multi-product portfolios.

• Proven ability to build and mentor high-performing teams and foster a culture of ethical AI use.

• Strong background in stakeholder management, especially in academic environments involving faculty, administrators, and IT leadership.

Domain Knowledge:

• Deep understanding of the Ed Tech Landscape, including challenges in student retention, personalized learning, and institutional efficiency.

• Familiarity with data-driven decision-making in academia and the use of analytics to improve student outcomes.

Key Competencies:

• Exceptional communication and storytelling skills for both technical and non-technical audiences.

• Strong analytical mindset with experience applying metrics for product success and institutional impact.

• Passion for educational equity and improving learning outcomes through data-driven technologies.

Experience in lieu of education

Equivalent relevant experience performing the essential functions of this job may substitute for education degree requirements.  Generally, equivalent relevant experience is defined as 1 year of experience for 1 year of education and is the discretion of the hiring manager.

 #LI-ZARD

Position & Application Details

Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.

How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.

Additional Information

Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive.

Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.

Equal Opportunity Employer: We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. #DEI