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.
Responsibilities:
• Support, maintain, and optimize existing AWS cloud workloads and infrastructure.
• ssist 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.
• utomate 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.
• utomate 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.
• 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.
What Would Be Nice to Have
• 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.
• bility to work independently and deliver technical work items with minimal oversight.
• Relevant AWS and/or Google Cloud certifications are preferred.
Technical Skills
Cloud Platforms: AWS, GCP
utomation/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
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