Senior DevOps Engineer (Terraform)

Company: Endava

Location: Remote, , United States (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-09-11

About this role

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.
 
By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.
 
From prototype to real-world impact - be part of a global shift by doing work that matters.

  • Design, build, and manage cloud infrastructure using Terraform.
  • Develop reusable Infrastructure as Code (IaC) modules and templates.
  • Architect and support cloud environments in AWS, Azure, or GCP.
  • Build and maintain CI/CD pipelines to automate application and infrastructure deployments.
  • Implement and support Docker and Kubernetes environments.
  • Develop automation using Python, Bash, or similar scripting languages.
  • Implement monitoring, logging, and alerting solutions.
  • Troubleshoot production infrastructure and provide on-call support as needed.
  • Collaborate with development, QA, and architecture teams to improve deployment and operational processes.
  • Apply DevOps best practices and support AI-enabled cloud initiatives.
  • Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
  • 5+ years of DevOps, Cloud Engineering, or Infrastructure Engineering experience.
  • Strong hands-on experience with Terraform.
  • Experience with AWS, Azure, or Google Cloud Platform (GCP).
  • Experience with Docker and Kubernetes.
  • Experience building CI/CD pipelines using Jenkins, GitLab CI, CircleCI, or similar tools.
  • Proficiency in Python, Bash, or other scripting languages.
  • Experience with configuration management tools such as Ansible, Puppet, or Chef.
  • Knowledge of cloud security, Infrastructure as Code, and DevOps best practices.
  • Familiarity with AI concepts including Machine Learning, Large Language Models (LLMs), ...

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