> Markdown version of [/jobs/ext/4660934-senior-cloud-platform-engineer](https://www.wearedevelopers.com/jobs/ext/4660934-senior-cloud-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Cloud Platform Engineer - **Company:** Dassault Systemes - **Location:** Woodbridge Township, NJ, United States - **Experience:** Expert - **Salary:** $114,750 - $153,000 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Microsoft Windows, Active Directory, Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Bash Shell, Ubuntu (Operating System), Mobile Application Development, Clinical Data Repository, Cloud Computing, Cloud Engineering, Data Files, Cursor, Linux, DevOps, File Systems, Github, Identity and Access Management, Python (Programming Language), Windows Servers, Peering, Performance Tuning, Windows PowerShell, Role-Based Access Control, Red Hat Enterprise Linux, Cloud Services, Prometheus, Zero Trust Network Access, Shell Script, Software Engineering, Pulumi, Google Cloud, Cloud Platform System, GitHub Copilot, Istio, Delivery Pipeline, Large Language Models, Grafana, Multi-Cloud, Amazon Virtual Private Cloud (VPC), Cloudformation, Gitlab-ci, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Linkerd (Service Mesh), Terraform, Microservices - **Published:** November 10, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-cloud-platform-engineer-iselin-nj--e01f2d56-55ac-4f54-948b-bc34b45616f4 ## About the Role Software Engineering, Cloud Computing, Clinical Trial, Patient Care, Data Sets, Clinical Data, Clinical Support, Mentoring, Ecosystems, Best Practices, * Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. * 5+ years of experience in Cloud Engineering, SRE, or DevOps, with deep proficiency in AWS and/or GCP. * Expert-level experience administering Linux (shell scripting, kernel tuning) and Windows Server (Active Directory, Group Policy, PowerShell). * Proven track record of running production-grade Kubernetes workloads at scale, including experience with Helm and container security. * Strong proficiency in Python, Go, or Bash for infrastructure automation and tool development. * Solid understanding of VPC/VNet design, peering, Transit Gateways, and zero-trust security models. Preferred Qualifications * Experience with "Cloud-Native" monitoring stacks (Prometheus, Grafana, ELK). * Background in migrating legacy Windows/Linux monolithic applications into containerized microservices. * Relevant certifications: AWS Solutions Architect Professional, Google Professional Cloud Architect, or Certified Kubernetes Administrator (CKA). ## Description * Design and implement secure, multi-account structures and landing zones across AWS, GCP, and Azure. * Manage and evolve multi-cloud IAM, SSO, and Role-Based Access Controls (RBAC) to ensure least-privilege access. * Enforce tagging standards, resource hierarchies, and cost-optimization strategies (rightsizing, idle resource elimination) to maintain fiscal accountability. * Lead the deployment, scaling, and management of Kubernetes clusters (EKS, GKE, or self-managed). Manage CNI plugins, ingress controllers, and service meshes (Istio/Linkerd). * Administer and optimize Linux (Ubuntu, Amazon Linux, RHEL) and Windows Server environments, ensuring hardened configurations and automated patching. * Manage the intersection of cloud services and traditional OS-level dependencies, including Active Directory integration and file system performance tuning. * Develop and maintain modular templates using Terraform, CloudFormation, or Pulumi. * Build and optimize deployment pipelines using GitHub Actions, GitLab CI, Flux, or ArgoCD to enable "GitOps" workflows. * Design security controls including encryption at rest/transit (KMS), VPC Service Controls, and audit logging to meet SOC2, HIPAA, or FedRAMP standards. * Leverage AI-native development tools (e.g., Cursor, GitHub Copilot) and LLM-powered agents to accelerate Infrastructure-as-Code (IaC) authoring, automate complex root-cause analysis, and proactively optimize cloud utilization through predictive anomaly detection.