AI DevOps Engineer: Cloud Automation & AI Platforms

NiCE; Sandy (UT); On-site; USD 120,000 - 160,000; Full time

Job summary

NiCE in Sandy, Utah, is hiring an AI DevOps Engineer to build AI-powered operational platforms that integrate monitoring, CI/CD, ticketing, and cloud infrastructure. You will design intelligent workflows, integrate AI models, and scale systems for automated tasks.

The role focuses on backend design, AI-enabled automation, and API/microservice development, with collaboration across product, SRE, and infrastructure teams.

Qualifications

• Strong experience in backend development with listed languages.
• Experience building scalable distributed systems in cloud environments.
• Familiarity with APIs, microservices, and event-driven systems.
• Exposure to AI/ML concepts, LLMs, or AI SDKs.
• Experience with AWS / Azure / GCP.
• Working knowledge of CI/CD, Docker, Kubernetes.
• Strong problem-solving and analytical skills.
• Ability to work in a fast-paced, evolving environment.

Responsibilities

• Design and develop scalable backend systems for AI-powered platforms.
• Build and maintain AI integrations, workflows, and automation pipelines.
• Implement REST APIs, microservices, and event-driven architectures.
• Work with both structured and unstructured data for AI use cases.
• Contribute to CI/CD pipelines, testing, and deployment automation.
• Troubleshoot and optimize production systems.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Contribute to reusable frameworks and engineering best practices.

Skills

Backend development

Typescript

C#

.NET

Python

Rust

Cloud

APIs

Microservices

Event-driven

AWS

Azure

GCP

CI/CD

Docker

Kubernetes

LLMs

AI SDKs

Problem solving

Analytical skills

Tools

Docker

Kubernetes

CI/CD

Job description

NiCE in Sandy, Utah, is hiring an AI DevOps Engineer to build AI-powered operational platforms that integrate monitoring, CI/CD, ticketing, and cloud infrastructure. You will design intelligent workflows, integrate AI models, and scale systems for automated tasks.

The role focuses on backend design, AI-enabled automation, and API/microservice development, with collaboration across product, SRE, and infrastructure teams.