Full Stack Aws Developer Jobs in Utah (NOW HIRING)

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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.