DevOps Engineer

Overview

On Site
Hybrid
BASED ON EXPERIENCE
Contract - W2
Contract - Independent
Contract - 5+ mo(s)

Skills

CI/CD
CONTINUOUS INTEGRATION
CONTINUOUS DELIVERY
JENKINS
GITHUB
GITLAB
TERRAFORM
TERRFORM
IAC
INFRASTRUCTURE
INFRASTRUCTURE AS CODE
PYTHON
BASH
SHELL
ATLASSIAN
JIRA
CONFLUENCE
BITBUCKET

Job Details

We are seeking a DevOps Engineer to build and operate modern SDLC platform components, automate provisioning, and integrate Atlassian Cloud tools with AI-enhanced developer workflows. This role will play a key part in implementing GenAI Integration within CI/CD pipelines, developer productivity tools, and release automation frameworks to accelerate software delivery and improve operational efficiency.

Key Responsibilities

  • Design, build, and maintain CI/CD pipelines, Infrastructure as Code (IaC), release automation, and platform integrations across tools such as Jira, Confluence, and Bitbucket.
  • Integrate GenAI capabilities into development pipelines and tools, including code generation, automated CI validations, and changelog creation.
  • Support model serving and inference infrastructure as needed to enable AI-driven workflows.
  • Implement and maintain SSO/MFA, user roles and permissions, observability, and platform hygiene automations (e.g., license management, project cleanup, secrets rotation).
  • Support integrations with ServiceNow, Identity Management, and SIEM logging solutions for compliance and traceability.

  • Collaborate cross-functionally with security, infrastructure, and software engineering teams to enhance platform performance, reliability, and developer experience
  • Required Qualifications
  • 3+ Years of DevOps, SRE, or platform engineering experience.
  • Proven expertise in CI/CD, Infrastructure as Code (Terraform or CloudFormation), Linux systems, and cloud environments ( AWS, Google Cloud Platform, or Azure).
  • Hands-on experience with Atlassian Cloud administration and automation.
  • Proficiency in integrating GenAI/LLM services into toolchains or workflows.
  • Strong scripting and automation skills using Python and Bash.
  • Working knowledge of containers and orchestration tools ( Docker, Kubernetes).

Preferred Qualifications

  • Experience managing or deploying LLM inference infrastructure and secure prompt-handling practices.
  • Familiarity with ModelOps concepts and lifecycle management.
  • Experience with enterprise Atlassian migrations or multi-instance integrations.
  • Understanding of security best practices for DevOps and AI-integrated systems.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.