Senior DevOps Cloud Engineer

GuidehouseBethesda, MD
$113,000 - $188,000Onsite

About The Position

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 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.

Requirements

  • Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
  • Bachelors' Degree
  • Minimum TEN (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.

Nice To Haves

  • 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.
  • Ability to work independently and deliver technical work items with minimal oversight.
  • Relevant AWS and/or Google Cloud certifications are preferred.

Responsibilities

  • 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 troubleshoot 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.

Benefits

  • Medical, Rx, Dental & Vision Insurance
  • Personal and Family Sick Time & Company Paid Holidays
  • Parental Leave
  • 401(k) Retirement Plan
  • Group Term Life and Travel Assistance
  • Voluntary Life and AD&D Insurance
  • Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
  • Transit and Parking Commuter Benefits
  • Short-Term & Long-Term Disability
  • Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
  • Employee Referral Program
  • Corporate Sponsored Events & Community Outreach
  • Care.com annual membership
  • Employee Assistance Program
  • Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service