Senior Software Engineer (AI-First, Full-Stack, AWS, Kubernetes)
Western Governors UniversityAbout the role
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:
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‑cal
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