Wgu
Staff AI Engineer
Raleigh, NC · Staff+ · Full-time
Work authorization required$161k-$250kDetected 7 days ago
PythonDatabricksAWSPlatform EngineeringMachine LearningData EngineeringData ScienceLLMsRAGAgentic AILLMOpsMLOpsResearchLeadershipCollaborationMentoringPublic Speaking
About the role
- 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.
- You will define how AI systems are architected, deployed, and scaled across the organization.
- Visa Sponsorship While we welcome applicants from all backgrounds, WGU is not able to provide visa sponsorship for this role.
Responsibilities
- Define and own AI engineering architecture standards, design patterns, and platform conventions for LLM-based systems
- Lead complex, cross-functional AI initiatives from inception through delivery, aligning engineering, product, data science, and research stakeholders
- Drive build-vs-buy and vendor evaluation decisions for AI frameworks, models, and infrastructure
- Design and scale internal AI platforms including shared tooling, reusable components, prompt libraries, and evaluation infrastructure
- Lead AI safety initiatives including red-teaming, adversarial testing, and responsible AI policy development
- Mentor and develop Senior and II-level engineers through coaching, design reviews, and technical leadership
- Demonstrated ability to define and drive architectural patterns and engineering standards at team or organizational scale
- Deep expertise in agentic system design including multi-agent architectures, state management, and reliability engineering for non-deterministic systems
- 5+ years of hands-on experience building and deploying LLM-based or AI systems in production at scale
Requirements
- experience and training
- All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.
- Strong proficiency in Python and software engineering fundamentals with a focus on quality, testing, and reliability standards
- Experience with AWS cloud architectures including scalable inference, data pipelines, and cost optimization
- Hands-on experience with fine-tuning, PEFT, and model evaluation in production environments
- Master's Degree or PhD in Computer Science, AI/ML, or a related field
- Experience with Databricks and related certifications
- Experience with open-source model ecosystems and self-hosted inference infrastructure
- Master's Degree strongly preferred.
Compensation
- $161,000.00 - $249,500.00
Benefits
- Bachelor's Degree in Computer Science, Software Engineering, Data Science, Machine Learning, Math, or a related field.
- 7+ years of experience in software engineering, data science, or machine learning
- AWS certifications such as AWS Certified Machine Learning - Specialty
Equal opportunity
- 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.
- Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.
Visa & Work Authorization
- While we welcome applicants from all backgrounds, WGU is not able to provide visa sponsorship for this role.
This listing is sourced directly from Wgu's careers page and normalized into a canonical job model.