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.

Required Qualifications

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