AI/ML DevSecOps Engineer: Build Secure AI Pipelines

CACI International Inc.; Denver (CO); On-site; USD 90,000 - 190,000; Full time

Job summary

CA C I International Inc. seeks a DevSecOps Engineer (AI/ML) to join its AI Center of Excellence in a fast-paced CTO organization.

You will build secure CI/CD pipelines, IaC, and deployment automation for production AI systems across cloud and on‑prem environments. You will deploy containerized workloads with Kubernetes and Docker, integrate security controls, and collaborate with program teams to operationalize AI capabilities in customer environments.

Qualifications

• Bachelor's degree or equivalent in a technical discipline.
• 5+ years of relevant engineering experience in DevSecOps or a similar role.
• Proven experience with CI/CD, Infrastructure as Code, automation, and secure software delivery.

Responsibilities

• Operate, secure, and improve the AI Center of Excellence's internal development infrastructure and engineering tools.
• Build and maintain secure CI/CD pipelines, Infrastructure as Code, deployment automation, and reusable infrastructure modules.
• Deploy, operate, and troubleshoot containerized applications using Kubernetes and Docker across cloud, on-premises, and classified environments.
• Integrate security, identity and access management, vulnerability management, and software supply chain controls throughout the delivery lifecycle.
• Implement monitoring, logging, tracing, and other observability capabilities for production systems.

Skills

DevSecOps

Kubernetes

Docker

Terraform

Python

Bash

AWS

Azure

CI/CD

Security

Education

Bachelor's degree in a related technical field

Tools

Kubernetes

Docker

Terraform

AWS

Azure

Job description

CA C I International Inc. seeks a DevSecOps Engineer (AI/ML) to join its AI Center of Excellence in a fast-paced CTO organization.

You will build secure CI/CD pipelines, IaC, and deployment automation for production AI systems across cloud and on‑prem environments. You will deploy containerized workloads with Kubernetes and Docker, integrate security controls, and collaborate with program teams to operationalize AI capabilities in customer environments.