Manager, AI and ML 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: Grade: Management Technical 715 Pay Range: $174,700.00 - $288,200.00 Job Description The Manager, AI and ML Engineering is a leader in building high-performing teams that turn AI opportunities into production-ready solutions. This leader combines strong people leadership, technical judgment, and a bias for delivery to guide the design, development, evaluation, and continuous improvement of AI applications and services. Working closely with Product, Engineering, Enterprise Data, Architecture, Security, and business partners, the manager translates strategy into execution, develops talent, establishes engineering excellence, and helps scale responsible AI across the university. Reporting to the Director, Enterprise AI Platforms, this role leads the AI Engineering team and supports the Director in advancing engineering strategy, technical standards, delivery practices, and organizational priorities across the broader Enterprise AI Platforms organization.   Essential Functions and Responsibilities: • Leads, develops, and inspires a high-performing team of AI Engineers through clear expectations, coaching, accountability, and purposeful career development. • Translates AI strategy and organizational priorities into an actionable team roadmap, delivery plans, and measurable outcomes. • Leads the design, development, testing, evaluation, deployment, and continuous improvement of production AI applications and services. • Establishes and reinforces engineering standards, design patterns, development practices, and quality expectations that improve reliability, scalability, security, and developer productivity. • Partners with the Director, Enterprise AI Platforms, to shape AI Engineering strategy, technical priorities, organizational planning, and cross-team initiatives. • Drives delivery of complex, high-impact AI initiatives, balancing near-term business outcomes with long-term technical sustainability. • Partners closely with AI Platform Operations and other technology teams to ensure AI solutions are production-ready, observable, secure, scalable, and operationally sustainable. • Collaborates with Product, Engineering, Enterprise Data, Architecture, Security, Legal, and business stakeholders to translate opportunities into practical AI solutions. • Provides technical leadership and guidance on generative AI, large language models, agentic systems, retrieval-augmented generation, AI application architecture, evaluation, and emerging AI technologies. • Builds reusable engineering capabilities, patterns, components, and practices that accelerate delivery and enable teams to develop AI solutions consistently. • Champions responsible AI engineering practices, including appropriate evaluation, security, privacy, governance, risk management, and quality controls. • Uses engineering metrics, product outcomes, quality measures, and operational signals to identify opportunities, manage risk, and continuously improve team performance and solution value. • Leads technical discussions and decisions, clearly articulating tradeoffs, recommendations, risks, and implications to technical and non-technical stakeholders. • Evaluates emerging AI technologies, development frameworks, models, tools, and vendor capabilities and translates relevant advances into practical engineering opportunities. • Creates a culture of innovation, experimentation, learning, and continuous improvement while maintaining a strong focus on delivery and production quality. • Represents AI Engineering with senior stakeholders and cross-functional partners, building trust and alignment around technical direction and delivery. • Mentors engineers and technical leaders across the broader organization and contributes to the development of enterprise AI engineering practices. • Communicates engineering strategy, progress, risks, outcomes, and recommendations clearly to the Director and other organizational leaders. Competencies: Organizational Impact • Leads a professional engineering team responsible for executing strategic and operational priorities with measurable impact on organizational outcomes. • Plans and prioritizes work, allocates team capacity, and removes barriers to effective delivery. • Contributes to workforce planning, resource decisions, vendor considerations, and investment discussions for the AI Engineering function. Problem Solving and Decision Making • Solves complex, ambiguous problems using strong technical judgment, structured analysis, experimentation, and practical engineering experience. • Makes sound decisions that balance business value, technical quality, security, risk, scalability, maintainability, and speed. • Anticipate