Role: Senior DevOps / Cloud Engineer
(AWS, GCP, AI Platform Operations)
Location: Remote - DMV
Position Summary
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.
Key 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 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.
Required Qualifications
- 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
Desired Characteristics
- 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.