Senior DevOps Engineer

Digital Links Inc
Ruther Glen, VA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Systems Engineering Bash Shell Cloud Computing Cloud Engineering Configuration Management System Configuration Continuous Delivery Continuous Integration DevOps Github
+29 more
Identity and Access Management Python (Programming Language) Key Management Cloud Services Ansible Runbook Software Deployment Data Logging Scripting Google Cloud Cloud Platform System Grafana Software Troubleshooting Multi-Cloud Git Cloudformation AI Platforms Gitlab-ci Kubernetes Infrastructure Automation Frameworks Information Technology Deployment Automation Machine Learning Operations Terraform Software Version Control Devsecops Docker Jenkins Vulnerability Analysis

Job description

We are seeking a highly skilled Senior DevOps / Cloud Engineer to support and enhance our existing AWS-based workloads while helping establish and expand our upcoming Google Cloud Platform (GCP) environment. This role requires deep hands-on expertise in cloud infrastructure, CI/CD, automation, application deployment, security, compliance-driven engineering, and AI platform deployment and configuration management. The ideal candidate will have strong experience in designing, building, automating, and supporting cloud-native and hybrid environments across AWS and GCP. This individual must be capable of working independently, owning technical deliverables end-to-end, and driving implementation of reliable, secure, scalable, and compliant DevOps practices., * Support, maintain, and optimize existing AWS cloud workloads and infrastructure.

  • Assist in building and operationalizing GCP support capabilities for new and future workloads.
  • Design, implement, and manage CI/CD pipelines for application and infrastructure delivery.
  • Deploy, manage, and troubleshooting applications across AWS and GCP environments.
  • Automate infrastructure provisioning, configuration management, and operational tasks using tools such as Ansible and Python.
  • Implement and support Infrastructure as Code and environment standardization practices.
  • Support deployment, configuration, and operational management of AI and ML platforms and supporting infrastructure in cloud environments.
  • Automate provisioning, configuration, and lifecycle management for AI-enabled infrastructure and services.
  • Collaborate with engineering and platform teams to enable secure, scalable, and compliant environments for AI workloads, without requiring hands-on AI application or model development.
  • Ensure cloud environments and deployment processes align with security and compliance requirements, including regulated frameworks such as FedRAMP or similar.
  • Monitor system health, availability, and performance, and proactively resolve operational issues.
  • Create and maintain technical documentation, runbooks, architecture diagrams, and standard operating procedures.

Independently manage assigned work items, priorities, and deliverables with minimal supervision.

  • Contribute to platform engineering best practices, cloud governance, and automation strategy.

Requirements

  • 10+ years of overall IT experience, with significant focus on DevOps, cloud engineering, systems engineering, or platform engineering.
  • Strong hands-on experience supporting and deploying workloads in AWS.
  • Working knowledge or hands-on experience with GCP, including deployment and support of applications and cloud services.
  • Proven experience designing and implementing CI/CD processes and tools in enterprise environments.
  • Strong hands-on experience with automation and scripting using Ansible and Python.
  • Experience deploying, configuring, and supporting applications in cloud environments.
  • Experience supporting AI and ML platform deployments and configuration management, focused on infrastructure, automation, and operations rather than application or model development.
  • Strong understanding of infrastructure automation, configuration management, release engineering, and platform operations.
  • Experience working in compliance-driven environments, such as FedRAMP, NIST-based environments, or similar regulated frameworks.
  • Experience with source control and DevOps toolchains such as Git, Jenkins, GitLab CI, GitHub Actions, or similar platforms.
  • Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
  • Strong troubleshooting, problem-solving, and root cause analysis skills.
  • Excellent verbal and written communication skills.
  • Ability to work independently and deliver technical work items with minimal oversight.

Preferred Qualifications

  • Experience with Terraform, CloudFormation, or other Infrastructure as Code tools.
  • Experience supporting AI/ML infrastructure and operational environments in cloud platforms.
  • Experience supporting multi-cloud environments.
  • Familiarity with cloud networking, IAM, secrets management, logging, and observability tools.
  • Experience with security scanning, policy enforcement, and DevSecOps practices.

Experience supporting cloud-native AI services, MLOps-enabling infrastructure, GPU-based workloads, or model hosting environments.

  • Familiarity with services such as Amazon SageMaker, Vertex AI, container-based AI platforms, or similar technologies.
  • Experience in government, healthcare, or other highly regulated environments.
  • Relevant AWS and/or Google Cloud certifications are preferred.

Technical Skills

  • Cloud Platforms: AWS, GCP
  • Automation/Scripting: Ansible, Python, Bash
  • CI/CD Tools: Jenkins, GitLab CI, GitHub Actions, or similar
  • Source Control: Git
  • Infrastructure as Code: Terraform, CloudFormation, CDK, GCP Deployment Manager or similar
  • Containers/Orchestration: Docker, Kubernetes
  • Compliance/Security: FedRAMP, NIST, security hardening, audit support
  • Monitoring/Logging: Cloud-native and third-party monitoring and observability tools, * Self-starter with a strong ownership mindset.
  • Able to independently plan and execute technical tasks.
  • Detail-oriented with strong documentation discipline.
  • Comfortable working in fast-paced, evolving cloud environments.
  • Strong collaboration skills across engineering, security, and operations teams.

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