DevOps Engineer

Job Title: DevOps Engineer

Location: Shelton, CT- Onsite

Job Description:

What you'll do

• Design, build, and maintain CI/CD pipelines that make software delivery fast, reliable, and repeatable across engineering teams
• Develop and maintain Infrastructure-as-Code with Terraform to provision and manage cloud and hybrid environments
• Develop reusable DevOps solutions—pipeline templates, Terraform modules, reference architectures, and implementation guidance—for adoption across multiple teams
• Define and maintain Git and version-control workflows, including enterprise branching strategies such as trunk-based development and GitFlow
• Apply AI to DevOps workflows, operations, documentation, and governance, with appropriate review and control points
• Partner across security/IAM, database, development, QA, and platform engineering teams to embed shared standards and best practices
• Provide documentation, enablement, and technical guidance to help teams adopt DevOps and automation best practices

Required

• Proven hands-on experience designing and maintaining CI/CD pipelines on GitHub Actions, Azure DevOps, Jenkins, or equivalent platforms
• Proficiency with Infrastructure-as-Code, particularly Terraform
• Strong scripting and automation skills in Python, Bash, or PowerShell
• Solid understanding of at least one major cloud platform (AWS or Azure)
• Experience defining and maintaining Git and version-control workflows, including enterprise branching strategies
• Track record of developing and documenting reusable DevOps solutions used across multiple teams
• Demonstrated experience applying AI to DevOps work—not just using AI coding assistants, but integrating AI into workflows, operations, and governance
• Ability to influence and drive adoption across teams without direct authority, through documentation, enablement, and practical examples
• Strong analytical and problem-solving skills with a focus on automation, reliability, and efficiency
• Experience working in Agile, cross-functional engineering environments

Preferred

• Experience building advanced AI-enabled DevOps capabilities—self-healing remediation, AI-generated IaC or pipeline scaffolding with human review gates, or internal AI tooling such as agents, MCP servers, or ChatOps for team self-service
• Hands-on experience with containerization and orchestration, including Docker, Kubernetes, or ECS
• Multi-cloud experience across both AWS and Azure
• Experience with observability and monitoring platforms, including Dynatrace, Datadog, Prometheus/Grafana, or Application Insights
• Experience with secrets management and policy-as-code tooling, including Key Vault, HashiCorp Vault, OPA, Sentinel, or Checkov
• Demonstrated ability to improve delivery flow—reducing cycle time and increasing release velocity—through pipeline and process optimization