Principal AI Platform Operations Engineer

WGU; Raleigh (NC); Hybrid; USD 202,000 - 313,000; Full time

Benefits offered by this job

Tuition discount

Wellbeing program

11 paid holidays and generous PTO

Job summary

Western Governors University (WGU) is seeking a leader to define and drive the AI operations strategy at scale. You will shape platform architecture, governance, and tooling while guiding executives on risk and investment priorities.

This role emphasizes cross-functional leadership, talent development, and external representation at industry venues. You will mentor engineers, publish technical guidance, and ensure compliance with regulatory standards while building a culture of reliability and

Qualifications

• Expertise in AI operations, deployment, observability, governance, and MLOps at scale.
• Ability to translate goals into architectural roadmaps and multi-year strategy.
• Deep knowledge of safety, risk, and regulatory considerations for enterprise AI.
• Proven ability to influence executive leadership and build consensus.
• Experience hiring and developing AI/ML teams and talent across levels.

Responsibilities

• Define multi-year AI operations vision aligned to WGU's mission.
• Establish reference architectures and governing principles for AI systems.
• Lead evaluation and adoption of frontier AI tooling and infra.
• Drive high-stakes AI operations programs across platforms and migrations.
• Advise executives on strategy, risk, and investment priorities.
• Define governance for responsible AI, model risk, security, and costs.
• Incubate new operational capabilities and sponsor PoC efforts.
• Serve as external technical spokesperson for AI ops work.
• Design and evolve the team's operating model and mentorship programs.
• Develop engineers through skill-building and knowledge sharing.

Skills

AI operations

strategic vision

frontier AI

model risk

executive influence

platform thinking

engineering culture

communication

talent development

cross-functional leadership

Education

Master's Degree in Computer Science or related

Tools

Databricks

AWS

Terraform

Kubernetes

Job description

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.

Pay Range: $202,000.00 - $313,000.00

Primary Responsibilities

• Defines the multi-year AI operations and platform technical vision and strategy for WGU, aligned to organizational mission and emerging technological opportunity.

• Establishes the foundational reference architectures and engineering principles that govern how AI/ML systems are deployed, operated, and governed across the organization.

• Leads the evaluation and adoption of frontier AI operations paradigms, tooling, and infrastructure; authors technical strategy documents and architectural decision records that guide org-wide direction.

• Drives the most complex, highest-stakes AI operations programs in the organization, including large-scale platform, migration, and reliability initiatives.

• Advises executives such as the Chief Technology Officer, VP of Engineering or Security, and senior product leadership on AI operations strategy, risk, and investment priorities.

• Defines AI operations governance including responsible AI standards, model risk management, security, cost accountability, and compliance frameworks for the organization.

• Identifies and incubates emerging operational capabilities; sponsors proof-of-concept initiatives that create future organizational leverage.

• Serves as the primary external technical spokesperson for WGU's AI operations work; represents the organization at industry conferences, in partnerships, and with strategic vendors.

• Designs and evolves the team's operating model, hiring criteria, competency framework, and engineering culture.

• Develops Staff, Senior, and II-level engineers through technical mentorship, sponsorship, and organizational knowledge-building programs.

• Authors internal and external thought leadership: technical blogs, whitepapers, architectural guides, and research contributions.

• Partners with legal, compliance, and privacy teams to ensure AI systems meet regulatory requirements and institutional risk standards.

• Performs other job-related duties as assigned.

This job description includes a general representation of job requirements rather than a comprehensive inventory of all required responsibilities or work activities. The contents of this document or related job requirements may change at any time with or without notice.

Qualifications

Knowledge, Skills, and Abilities

• Recognized expertise across the full spectrum of AI operations: deployment, platform engineering, observability, reliability engineering, governance, and LLMOps/MLOps at enterprise scale.

• Ability to define and communicate multi-year technical strategy; translate organizational goals into architectural vision and operational roadmaps.

• Deep expertise in frontier AI operations practices and the ability to assess, adapt, and productionize emerging techniques at organizational scale.

• Expert-level knowledge of AI safety, responsible AI, model risk, security, and enterprise AI governance including regulatory and compliance considerations.

• Proven ability to influence organizational direction at the executive level; able to build consensus across competing priorities and stakeholders.

• Strong platform and systems thinking: ability to design AI infrastructure that enables teams to move faster and build more reliably.

• Track record of establishing engineering culture, standards, and practices that durably improve organizational capability.

• Exceptional written and verbal communication; able to author technical strategy documents, present to boards and executives, and represent the organization externally.

• Experience in technical hiring, team-building, and developing talent across multiple seniority levels.

• Deep familiarity with the AI operations vendor landscape, open-source ecosystem, and technology frontier; able to make informed, timely, well-reasoned bets.

• Strong cross-functional leadership; comfortable driving alignment across engineering, product, data science, legal, and executive stakeholders.

Education

• Master's Degree in Computer Science, Software Engineering, Data Science, Machine Learning, Math, Physics, or a related field

Experience

• 7+ years of hands‑on experience deploying and operating ML/AI systems in production at scale.

• 5 years of experience working in an AI/ML context alongside Data Scientists or ML Engineers

• 3 years of experience in building large‑scale machine learning or deep learning models on a cloud platform

• Demonstrated experience setting operational strategy or architectural vision at an organizational level.

• Proven track record of delivering transformative AI platform or operations programs that produced measurable business impact.

• Experience advising or influencing senior/executive leadership on AI operations strategy and investment.

• Experience leading or significantly contributing to AI governance, responsible AI, or model risk frameworks.

• Experience building and scaling AI engineering or operations teams, including hiring, competency‑building, and culture‑setting.

• Experience representing an organization externally through conference talks, publications, or strategic partnerships.

• Deep hands‑on expertise in production AI reliability engineering, observability, and deployment at scale.

Preferred Qualifications

• 10+ years of experience in software engineering, data science, or machine learning.

• Experience with the Databricks platform; Databricks certifications (e.g., Databricks Certified Machine Learning Professional, Databricks Certified Data Engineer, or Databricks Certified Associate Developer for Apache Spark) are a plus.

• AWS cloud platform experience; AWS certifications (e.g., AWS Certified Machine Learning, Specialty, AWS Certified DevOps Engineer) a plus.

• Experience with infrastructure‑as‑code (Terraform, CloudFormation) and container orchestration (Kubernetes) for AI/ML workloads.

• Experience in EdTech, personalized learning, or student‑facing AI/ML platforms.

• Experience with enterprise AI governance and compliance frameworks (FERPA, GDPR, etc.).

• Contributions to open‑source MLOps/LLMOps tooling, or published work and conference presentations in the AI/ML operations domain.

• PhD in Computer Science, AI/ML, or a related field.

• Experience operating in highly regulated environments (e.g., EdTech, healthcare, finance) with associated compliance requirements.

• Recognized thought leadership in the AI/MLOps community through writing, speaking, or advisory roles.

This position requires occasional travel of up to 20%, including required attendance at designated company summits (typically one to two per year). Additional travel may include conferences, visits to company locations, and other business‑related events as needed. Additional travel may be assigned as needed to support business requirements.

#LI-AW2

Additional Information

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.

• 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 [e-mail].
• Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.