Principal AI Platform Operations Engineer
Western Governors University2 hours ago
Raleigh, NC, USAStaff+
Base Salary
$202k - $313k/yr
Responsibilities
- Define WGU’s multi-year AI operations and platform vision, strategy, reference architectures, and engineering principles.
- Lead complex enterprise-scale AI platform, migration, reliability, deployment, observability, and operational initiatives.
- Establish governance for responsible AI, model risk, security, cost accountability, compliance, and regulatory requirements.
- Advise executive and senior product leadership on AI operations strategy, risk, and investment priorities.
- Evaluate and adopt emerging AI operations tooling, infrastructure, and operational capabilities.
- Design the team operating model, hiring criteria, competency framework, and engineering culture.
- Mentor and develop Staff, Senior, and II-level engineers through technical guidance, sponsorship, and knowledge-building programs.
- Represent WGU’s AI operations work externally through conferences, partnerships, strategic vendors, technical publications, and thought leadership.
- Partner with legal, compliance, and privacy teams to ensure AI systems meet institutional risk and regulatory standards.
Requirements
- Master’s degree in Computer Science, Software Engineering, Data Science, Machine Learning, Mathematics, Physics, or a related field.
- At least 7 years of hands-on experience deploying and operating ML/AI systems in production at scale.
- At least 5 years of experience working in an AI/ML context alongside Data Scientists or ML Engineers.
- At least 3 years of experience building large-scale machine learning or deep learning models on a cloud platform.
- Demonstrated experience setting organizational-level operational strategy or architectural vision and delivering transformative AI platform or operations programs.
- Experience advising or influencing senior and executive leadership on AI operations strategy and investment.
- Experience contributing to AI governance, responsible AI, model risk, team building, technical hiring, competency development, and engineering culture.
- Deep hands-on expertise in production AI reliability engineering, observability, and deployment at scale.
- Preferred qualifications include 10+ years in software engineering, data science, or machine learning; Databricks and AWS experience or certifications; Terraform, CloudFormation, and Kubernetes experience; and experience with regulated environments, enterprise AI governance, open-source MLOps/LLMOps tooling, publications, or conference presentations.
- A PhD in Computer Science, AI/ML, or a related field and recognized AI/MLOps thought leadership are preferred.
Benefits
- Full-time regular position with eligibility for bonuses.
- Medical, dental, vision, telehealth, mental healthcare, health savings account, and flexible spending account benefits.
- Life insurance, disability coverage, accident, critical illness, hospital indemnity, legal, and identity theft coverage.
- Retirement savings plan, wellbeing program, and discounted WGU tuition.
- Flexible paid time off, flexible paid sick time, 11 paid holidays, and other paid leave including up to 12 weeks of parental leave.
- Occasional travel of up to 20%, including company summits, conferences, company-location visits, and other business events.
- The position is classified as a regular role with 40 standard weekly hours.