Job description
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.
What You’ll Do
Define and lead WGU’s enterprise AI architecture strategy, including reference architectures, standards, and best practices.
Establish patterns for integrating AI, ML, and generative AI solutions into enterprise systems in a secure, scalable, and maintainable way.
Architect AI-enabled solutions such as recommendation systems, intelligent assistants, and automation workflows that align to institutional priorities.
Define reusable AI services and platforms, including model serving, prompt orchestration, inference pipelines, and shared enablement capabilities.
Strengthen the data and integration foundations that support AI, including pipelines, data quality, feature engineering readiness, APIs, microservices, and event-driven patterns.
Enable real-time and adaptive AI use cases by designing event contracts, streaming architectures, and feedback loops that are interoperable across domains.
Establish responsible AI and governance frameworks that support ethical, secure, and compliant AI usage, including privacy considerations and FERPA alignment.
What You’ll Bring
10 plus years of experience in software engineering, architecture, or related roles, with increasing focus on AI and ML systems.
3 years of experience as an Enterprise Architect or Solution Architect, or 8 years in a technical leadership role such as technical lead or principal engineer.
Proven experience designing enterprise-scale distributed systems and delivering successful technology transformation.
Proven experience designing and deploying AI, ML, or generative AI solutions at scale.
Strong expertise in AI and ML architecture, including training, inference, and deployment patterns.
Strong expertise in APIs and microservices patterns used to integrate AI capabilities into enterprise applications.
Strong expertise with distributed systems and cloud platforms such as AWS, Azure, or GCP, including architectural tradeoffs and scalability considerations.
Bonus Points
Experience with LLMs, prompt engineering, RAG architectures, and vector databases.
Familiarity with MLOps tools and frameworks such as MLflow, SageMaker, or Vertex AI.
Familiarity with modern data stack tools such as Snowflake, Databricks, dbt, or Kafka, and how they support AI workloads.
Experience in Lieu of Education
WGU considers a combination of relevant education, certifications, and directly related experience when evaluating qualifications for this role.
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 team interview
Work Location
This is a full-time, hybrid role based in our Salt Lake City, Utah office.
Visa Sponsorship
While we welcome applicants from all backgrounds, WGU is not able to provide visa sponsorship for this role.
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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.