Senior AI Engineer
About The Position
WGU is seeking a Senior AI Engineer to join their AI Engineering Enablement team. This role will be pivotal in shaping the next generation of intelligent, scalable systems. The Senior AI Engineer will lead the design and delivery of complex AI solutions impacting innovation across the organization. Responsibilities include acting as a technical anchor for the team, driving architecture, reliability, and excellence in production AI systems, mentoring others, and influencing long-term technical direction. The position is full-time and requires five days per week in the Raleigh, NC office.
Requirements
- 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
Nice To Haves
- 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
Responsibilities
- 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
Benefits
- 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
- 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
- other paid leaves, including up to 12 weeks of parental leave
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
