Senior AI Engineer
Job Description
Join WGU’s AI Engineering Enablement team and play a pivotal role in shaping the next generation of intelligent, scalable systems. As a Senior AI Engineer, you will lead the design and delivery of complex AI solutions that directly impact innovation across the organization. You’ll act as a technical anchor for the team, driving architecture, reliability, and excellence in production AI systems while mentoring others and influencing long-term technical direction.
What You’ll Do
- Lead end-to-end design and delivery of production LLM-powered applications and multi-agent systems from architecture through deployment and monitoring
- Own and evolve critical AI infrastructure, ensuring reliability, scalability, and observability standards
- Architect and optimize advanced RAG pipelines, including hybrid retrieval, re-ranking, and multi-index strategies
- Design and implement AI evaluation frameworks, including automated regression testing, LLM-as-judge workflows, and red-teaming protocols
- Drive prompt engineering strategy for complex multi-turn and multi-agent interactions, including governance and versioning practices
- Mentor AI engineers and elevate team standards through design reviews, code reviews, and technical guidance
What You’ll Bring
- 5+ years of experience in software engineering, data science, or machine learning
- 3+ years of hands-on experience building and deploying LLM-based applications or AI systems in production
- Strong experience building and deploying production LLM-powered applications using major APIs and/or open-source models
- Advanced expertise in RAG pipeline design, embedding strategies, and retrieval optimization
- Experience designing scalable evaluation frameworks, including automated testing and quality measurement
- Proficiency in Python and strong software engineering fundamentals, including system design and CI/CD practices
- Experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent) in production contexts
- Ability to lead complex technical discussions, mentor others, and operate effectively in fast-moving environments
Bonus Points
- Experience with Databricks or related certifications
- Experience with open-source model ecosystems (Hugging Face, Ollama, vLLM) and self-hosted inference infrastructure
- Experience with AWS and cloud-native AI infrastructure
- Background in EdTech, personalized learning, or student-facing AI applications
Experience In Lieu Of Education
An equivalent combination of relevant education and experience performing advanced AI engineering work will be considered.
Work Location
This is a full-time, in-office position requiring five days per week in our Raleigh, NC office, designed to foster the collaboration and connection that fuel our best work.
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.