New

Senior AI Engineer

Western Governors University
life insurance, flexible benefit account, parental leave, paid time off, paid holidays, sick time
United States, North Carolina, Raleigh
Jul 15, 2026
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: Technical 411 Pay Range: $161,000.00 - $249,500.00 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 Lead model fine-tuning and adaptation initiatives using techniques such as LoRA, PEFT, and RLHF 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 Deep knowledge of agentic AI systems including tool use, memory architectures, and multi-agent coordination 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. At WGU, our mission drives everything we do, including how we hire. Our interview experience is designed to give qualified candidates the opportunity to show their best work through meaningful conversations and collaboration. We thoughtfully review every application and invite forward the candidates whose experience and potential best align with the role and our mission. Introductory call with a Talent Partner Hiring manager interview Technical interview with senior team member Team panel interview with live coding exercise 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. Visa Sponsorship While we welcome applicants from all backgrounds, WGU is not able to provide visa sponsorship for this role. Equivalents and Substitutions Equivalent relevant experience may substitute for degree requirements (1 year of experience per year of education at the discretion of the Hiring Manager). #LI-AW2 Position & Application Details 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. 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. Additional Information 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 recruiting@wgu.edu. Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.