Senior Software Engineer (AI-First, Full-Stack, AWS, Kubernetes)

Job Type: Full time

Job Number: JR-025155

Location: Salt Lake City,
UT

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 410 Pay Range: $140,200.00 – $217,200.00

Job
Description

Role Overview

We are seeking a Senior
Software Engineer who thrives in ambiguous problem spaces and excels at technical research, discovery, and analysis. This role requires
strong end-to-end engineering skills across frontend and backend systems, along with hands-on experience designing and delivering AI-powered
applications using Large Language Models (LLMs) deployed on AWS and Kubernetes.

In this role, you will lead technical
discovery efforts, explore emerging approaches, and translate loosely defined problems into scalable, production-ready solutions. You will
work closely with product, design, and engineering partners to shape user-facing experiences and cloud-native, containerized platform
capabilities.

This is a hands-on senior individual contributor role with strong ownership of architecture, delivery, and
mentoring.

What You’ll Do

Technical Discovery & Research

• Lead research and discovery for complex,
  ambiguous problem spaces through architectural spikes, prototypes, and proof-of-concepts

• Evaluate new technologies,
  AWS services, Kubernetes patterns, and AI capabilities

  
  

• Perform build-vs-buy and managed-service vs.
  self-managed tradeoff analyses

• Translate findings into clear architectural direction and implementation plans

  
  

AI & Large Language Models

• Design, implement, and evaluate AI-powered features using Large Language
  Models

  
  

• Apply prompt engineering, retrieval-augmented generation (RAG), and agent-based workflows

• Design
  AI systems that account for latency, cost, reliability, observability, and safety

  
  

• Deploy AI services in
  containerized environments and integrate them with cloud-native infrastructure

• Stay current with applied AI/LLM
  advancements and production best practices

  
  

Full-Stack Engineering

• Own features end-to-end, from
  frontend experiences to backend services and data layers

  
  

• Build modern, responsive user interfaces using Angular, or similar
  frameworks

• Design and implement scalable backend services and APIs

  
  

• Ensure solutions meet high standards for
  performance, reliability, security, and maintainability

AWS, Kubernetes & Cloud-Native
Architecture

• Design, deploy, and operate cloud-native systems on AWS using Kubernetes

• Build
  and operate containerized workloads using Docker and Kubernetes (EKS or equivalent)

  
  

• Design Kubernetes
  deployments, services, ingress, autoscaling, and resource management strategies

• Implement secure, highly available
  architectures using AWS and Kubernetes best practices

  
  

• Apply Infrastructure as Code using tools such as
  Terraform and Helm

• Monitor, troubleshoot, and optimize distributed systems using cloud and Kubernetes observability
  tools

  
  

DevOps & Reliability

• Design and maintain CI/CD pipelines that build, test, and deploy
  containerized applications

  
  
• 
  

  Support zero-downtime deployments and safe rollout strategies (e.g., blue/green,
  canary)

• Participate in on-call rotations and incident response for production systems

  
  

• Drive improvements in
  reliability, scalability, and developer experience

Leadership & Collaboration

• Provide technical
  leadership on projects and guide architectural decisions

• Mentor engineers through design reviews, code reviews, and hands-on
  collaboration

  
  

• Partner with product managers and designers to align technical solutions with user
  needs

• Communicate clearly about technical tradeoffs, risks, and system behavior

  
  

What We’re Looking
For

Required Qualifications

• 6+ years of professional software engineering
  experience

• Bachelor’s Degree – equivalent relevant experience performing the essential functions of this job may substitute
  for education degree requirements

  
  
• 
  

  Strong proficiency in a modern backend language (e.g., Java, Kotlin,
  Python, or similar)

• Strong frontend experience with Angular, or equivalent frameworks

  
  

• Significant
  experience building and operating production systems on AWS

• Hands-on experience deploying and managing applications on
  Kubernetes

  
  

• Proven ability to work in ambiguous problem spaces and drive clarity via research and
  experimentation

• Experience building or integrating AI-powered features using Large Language Models

  
  

Kubernetes & Cloud-Native Experience

• Experience with Kubernetes fundamentals: pods, deployments,
  services, ingress, and autoscaling

  
  

• Experience running production workloads on EKS or comparable Kubernetes
  platforms

• Familiarity with container security, resource optimization, and operational best
  practices

  
  

• Experience debugging and operating distributed systems in containerized environments

AI
& Discovery Experience

• Experience with prompt design, evaluation, and iterative
  experimentation

• Familiarity with RAG architectures, tool-using agents, or workflow orchestration

  
  

• Ability to
  reason critically about AI behavior rather than treating models as black boxes

Preferred Qualifications

• Experience building SaaS or platform products using AWS and Kubernetes

• Experience with service
  meshes, event-driven architectures, or workflow orchestration

  
  

• Experience influencing technical strategy or platform
  architecture

• Prior experience mentoring engineers or leading cross-team initiatives

  
  

How You’ll Be
Successful in This Role

• You enjoy tackling poorly defined problems and discovering the right solution

  
  

• You
  balance experimentation with engineering rigor

• You make thoughtful architectural decisions grounded in tradeoffs and
  data

  
  

• You care deeply about production reliability, maintainability, and user experience

• You are excited about
  applying AI and cloud-native technologies responsibly and at scale

  
  

• You enjoy coaching and helping others mature in
  their roles

Why Join Us

• Work on complex problems where discovery, AI, and cloud-native
  architecture matter

• Shape how AI systems are deployed and scaled on Kubernetes

  
  

• Collaborate with
  experienced engineers and product leaders

• Have real influence over system architecture and technical
  direction

  
  

• Continue growing as a senior technologist while staying hands-on

Job Description Disclaimer: This
position description provides the major duties/responsibilities, requirements and working conditions for the position. It is intended to be
an accurate reflection of the current position, however management reserves the right to revise or change as necessary to meet
organizational needs. Other responsibilities may be assigned when circumstances require.

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.

LI-JW1

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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