Senior DevOps / Cloud Engineer (AWS, GCP, AI Platform Operations)

Job Description

Job Description

Senior DevOps / Cloud Engineer

(AWS, GCP, AI Platform Operations)

We are seeking a highly skilled and experienced candidate that can either take over the day-to-day architectural and operational project of moving new projects into AWS as lead -OR- can do the equivalent leading us into Google Cloud Platform (GCP) environment at the same level of complexity as exists for our AWS implementation . 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

· 12+ 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.

Preferred US citizens, GC holders and candidates from DMV area.