Senior DevOps Engineer

Snowrelic Inc; United States; Teletrabalho; USD 140 000 - 210 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Remote-friendly

Competitive compensation

Resumo da oferta

Snowrelic Inc. is seeking a highly skilled Senior DevOps / Cloud Engineer to support and optimize AWS workloads while expanding a GCP environment.

You will design, build, automate, and operate cloud-native and hybrid systems with a focus on security and compliance. The ideal candidate will have hands-on experience in CI/CD, automation, AI platform deployment, and configuration management across AWS and GCP.

Qualificações

• 10+ years of IT/DevOps experience in cloud environments.
• Hands-on AWS deployment and operations.
• Experience with GCP, CI/CD, IaC, and security/compliance.

Responsabilidades

• Design, build, and optimize CI/CD pipelines across AWS and GCP.
• Automate provisioning and configuration management.
• Ensure security, compliance, and observability across platforms.

Conhecimentos

AWS

GCP

CI/CD

Ansible

Python

Terraform

Docker

Kubernetes

Security

Compliance

Git

Jenkins

GitHub Actions

Ferramentas

Git

Jenkins

GitLab CI

GitHub Actions

Descrição da oferta de emprego

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.

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.