Senior DevOps Cloud Engineer

STAFFXPERT LLC is seeking a Senior DevOps Cloud Engineer on behalf of our client in Bethesda, MD to support and enhance existing AWS workloads while helping establish and expand a GCP environment. This role will focus on cloud infrastructure, CI/CD, automation, application deployment, security, compliance, and the infrastructure and operational support of AI/ML platforms. The ideal candidate is a hands-on cloud and DevOps professional who can independently own technical deliverables and implement secure, reliable, scalable, and compliant solutions across AWS and GCP environments. Key Responsibilities

• Support, maintain, optimize, and troubleshoot AWS cloud workloads and infrastructure.
• Help build and operationalize GCP capabilities for new and future workloads.
• Design, implement, and manage enterprise CI/CD pipelines for applications and infrastructure.
• Deploy, configure, manage, and troubleshoot applications across AWS and GCP.
• Automate infrastructure provisioning, configuration management, and operational processes using Ansible, Python, and Bash.
• Implement Infrastructure as Code and environment standardization practices.
• Support deployment and configuration of AI/ML platforms and associated cloud infrastructure, with a focus on infrastructure and operations rather than model development.
• Automate provisioning and lifecycle management for AI-enabled infrastructure and services.
• Ensure cloud environments and deployment processes align with security and compliance requirements, including FedRAMP, NIST-based, or similar regulated frameworks.
• Monitor system health, availability, and performance and proactively resolve operational issues.
• Apply DevSecOps practices, security hardening, and policy enforcement as appropriate.
• Develop and maintain technical documentation, runbooks, architecture diagrams, and standard operating procedures.
• Collaborate with engineering and platform teams to deliver secure, scalable, and compliant cloud environments.
• Independently manage assigned priorities, technical work items, and deliverables with minimal supervision.
• Contribute to cloud governance, platform engineering standards, and automation strategies.

• Strong hands-on experience supporting and deploying workloads in AWS.
• Working knowledge or hands-on experience with GCP and cloud application deployment.
• Proven experience designing and implementing enterprise CI/CD processes and pipelines.
• Strong automation and scripting experience with Ansible and Python.
• Experience deploying, configuring, and supporting applications in cloud environments.
• Experience supporting AI/ML infrastructure and platforms from an infrastructure, automation, and operations perspective.
• Strong understanding of infrastructure automation, configuration management, release engineering, and platform operations.
• Experience working in compliance-driven environments such as FedRAMP, NIST-based, or similar regulated environments.
• Experience with Git and DevOps toolchains such as Jenkins, GitLab CI, GitHub Actions, or similar technologies.
• Knowledge of Docker and Kubernetes.
• Strong troubleshooting, problem-solving, and root cause analysis skills.
• Excellent written and verbal communication skills.
• Ability to work independently and manage technical deliverables with minimal oversight.

Preferred Qualifications

• Experience with Terraform, CloudFormation, CDK, or other Infrastructure as Code technologies.
• Experience supporting multi-cloud environments.
• Experience with cloud networking, IAM, secrets management, logging, and observability.
• Experience with security scanning, policy enforcement, and DevSecOps practices.
• Experience supporting GPU-based workloads, model hosting environments, MLOps infrastructure, or cloud-native AI services.
• Familiarity with Amazon SageMaker, Vertex AI, container-based AI platforms, or similar technologies.
• Experience supporting government, healthcare, or other highly regulated environments.
• Relevant AWS and/or Google Cloud certifications.

Technical Environment

• Cloud: AWS, GCP
• Automation/Scripting: Ansible, Python, Bash
• CI/CD: Jenkins, GitLab CI, GitHub Actions, or similar
• Source Control: Git
• Infrastructure as Code: Terraform, CloudFormation, CDK, GCP deployment tools, or similar
• Containers: Docker, Kubernetes
• Security & Compliance: FedRAMP, NIST, security hardening, audit support
• Monitoring & Observability: Cloud-native and third-party monitoring and logging platforms