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 teamsDevelop and maintain Infrastructure-as-Code with Terraform to provision and manage cloud and hybrid environmentsDevelop reusable DevOps solutions—pipeline templates, Terraform modules, reference architectures, and implementation guidance—for adoption across multiple teamsDefine and maintain Git and version-control workflows, including enterprise branching strategies such as trunk-based development and GitFlowApply AI to DevOps workflows, operations, documentation, and governance, with appropriate review and control pointsPartner across security/IAM, database, development, QA, and platform engineering teams to embed shared standards and best practicesProvide 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 platformsProficiency with Infrastructure-as-Code, particularly TerraformStrong scripting and automation skills in Python, Bash, or PowerShellSolid understanding of at least one major cloud platform (AWS or Azure)Experience defining and maintaining Git and version-control workflows, including enterprise branching strategiesTrack record of developing and documenting reusable DevOps solutions used across multiple teamsDemonstrated experience applying AI to DevOps work—not just using AI coding assistants, but integrating AI into workflows, operations, and governanceAbility to influence and drive adoption across teams without direct authority, through documentation, enablement, and practical examplesStrong analytical and problem-solving skills with a focus on automation, reliability, and efficiencyExperience 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-serviceHands-on experience with containerization and orchestration, including Docker, Kubernetes, or ECSMulti-cloud experience across both AWS and AzureExperience with observability and monitoring platforms, including Dynatrace, Datadog, Prometheus/Grafana, or Application InsightsExperience with secrets management and policy-as-code tooling, including Key Vault, HashiCorp Vault, OPA, Sentinel, or CheckovDemonstrated ability to improve delivery flow—reducing cycle time and increasing release velocity—through pipeline and process optimization