Senior AI Engineer

Job Type: Full time

Job Number: JR-025030

Location: Raleigh, NC

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).

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.

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