Staff AI Engineer

Job Type: Full time

Job Number: JR-025691

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 412 Pay Range: $161,000.00 – $249,500.00

Job Description

As
a Staff AI Engineer, you will serve as a technical leader and force multiplier within the AI Engineering Enablement team. You will define
how AI systems are architected, deployed, and scaled across the organization. Operating at the intersection of deep technical expertise and
organizational leadership, you will shape platform strategy, influence roadmaps, and elevate engineering capabilities across multiple teams.

What You’ll Do

• 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
• Establish and mature LLMOps practices including governance, cost management, observability, and safe
  deployment standards
• 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

What You’ll Bring

• Expert-level, production-proven experience across the AI engineering stack
  including LLM APIs, agentic systems, RAG pipelines, evaluation frameworks, and LLMOps
• 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
• Strong platform engineering
  experience designing shared infrastructure, reusable tooling, and developer-facing systems
• Advanced knowledge of LLM fine-tuning,
  alignment techniques, and evaluation methodologies including safety and bias assessment
• Experience leading vendor evaluations and
  technical due diligence for AI frameworks and infrastructure
• Strong proficiency in Python and software engineering fundamentals with
  a focus on quality, testing, and reliability standards
• Bachelor’s Degree in Computer Science, Software Engineering, Data Science,
  Machine Learning, Math, or a related field. Master’s Degree strongly preferred.
• 7+ years of experience in software engineering, data
  science, or machine learning
• 5+ years of hands-on experience building and deploying LLM-based or AI systems in production at
  scale
• Demonstrated experience setting architectural direction across teams or organizations
• Experience leading complex AI
  projects across multiple teams or functional areas
• Proven mentorship of Senior and/or II-level engineers
• Experience
  designing and operating shared AI platforms or internal AI infrastructure
• Experience owning LLMOps or MLOps practices including
  governance, rollout strategy, and production monitoring
• 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

Bonus Points

• Master’s Degree or PhD in Computer Science, AI/ML, or a related
  field
• Experience with Databricks and related certifications
• AWS certifications such as AWS Certified Machine Learning –
  Specialty
• Experience with open-source model ecosystems and self-hosted inference infrastructure
• Experience in EdTech,
  personalized learning, or student-facing AI platforms
• Published research, conference presentations, or open-source contributions in
  AI/ML
• Experience with enterprise AI governance, compliance frameworks, or regulatory requirements

Experience in
Lieu of Education

Equivalent relevant experience performing the essential functions of this job may substitute for
graduate education degree preferences or requirements.

What to Expect

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
• Hiring manager
  interview
• Technical interview
• Final panel interview

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.

Travel Requirement

This position requires
occasional travel of up to 20%, including required attendance at designated company summits (typically one to two per year). Additional
travel may include conferences, visits to company locations, and other business-related events as needed. Additional travel may be assigned
as needed to support business requirements.

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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