DevOps Engineer

Brooksource; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Brooksource is seeking a DevOps Engineer to support a high-visibility Nuclear Online Work Management initiative. The role focuses on building a production foundation within a governed Databricks and Azure environment, automating deployments, and ensuring secure, reliable operations.

You will collaborate with engineering, data, and architecture teams to optimize CI/CD pipelines, IaC, and deployment tooling while maintaining strong governance and security practices in a highly regulated enterprise

Qualifications

• 4+ years of DevOps, Cloud, Platform, SRE, or related engineering experience in enterprise environments.
• Strong DevOps fundamentals across CI/CD, Git, release management, environment management, and production support.
• Experience building and maintaining enterprise CI/CD pipelines.
• Experience with Infrastructure as Code (IaC) using Terraform or similar tools.
• Hands-on experience with cloud infrastructure, preferably Azure.
• Understanding of enterprise security, IAM, secrets management, networking, and change controls.

Responsibilities

• Build and maintain enterprise CI/CD pipelines supporting the Nuclear Online Work Management initiative.
• Automate application, infrastructure, and environment deployments using established enterprise tooling.
• Partner with AI and data engineers to move Databricks and AI solutions into production.
• Support the environment and implementation work for the team’s Databricks, Python, Docker, and Kubernetes stack.
• Ensure deployments align with the client’s engineering, security, governance, and operational standards.
• Implement and support monitoring, logging, alerting, and observability.
• Troubleshoot infrastructure, deployment, integration, and production issues.

Skills

CI/CD

Git

Terraform

Azure

Kubernetes

Python

Monitoring

Tools

Databricks

Docker

Job description

Brooksource is seeking a DevOps Engineer to support a high-visibility Nuclear Online Work Management initiative at one of our largest Fortune 200 energy clients. This program is modernizing nuclear work management while introducing Generative AI and Agentic AI capabilities into critical operational processes, built within the client’s governed Databricks and Azure environment.

The DevOps Engineer will help build and support the production foundation for these emerging solutions partnering with the engineering, data, and architecture teams to automate deployments, support infrastructure, and ensure solutions are secure, reliable, and production-ready. Day to day, this includes the environment and implementation work around the team’s Databricks, AI/ML, Python, Docker, and Kubernetes stack. Strong DevOps fundamentals and experience operating within complex, highly-governed enterprise environments are the priority. The ideal candidate can quickly learn and conform to the client’s established engineering, DevOps, security, and governance practices.

Responsibilities

• Build and maintain enterprise CI/CD pipelines supporting the Nuclear Online Work Management initiative.
• Automate application, infrastructure, and environment deployments using established enterprise tooling.
• Partner with AI and data engineers to move Databricks and AI solutions into production.
• Support the environment and implementation work for the team’s Databricks, Python, Docker, and Kubernetes stack.
• Ensure deployments align with the client’s engineering, security, governance, and operational standards.
• Implement and support monitoring, logging, alerting, and observability.
• Troubleshoot infrastructure, deployment, integration, and production issues.

Required Qualifications

• 4+ years of DevOps, Cloud, Platform, SRE, or related engineering experience in enterprise environments.
• Strong DevOps fundamentals across CI/CD, Git, release management, environment management, and production support.
• Experience building and maintaining enterprise CI/CD pipelines.
• Experience with Infrastructure as Code (IaC) using Terraform or similar tools.
• Hands-on experience with cloud infrastructure, preferably Azure.
• Understanding of enterprise security, IAM, secrets management, networking, and change controls.

Preferred Qualifications

• Experience with Databricks or other data platforms.
• Exposure to Generative AI, LLMs, RAG, or Agentic AI.
• Experience supporting AI/ML, MLOps, or data engineering workloads.
• Experience with Python, Docker, and/or Kubernetes.
• Experience within highly governed or regulated enterprise environments (e.g., nuclear, utilities, defense, financial services, healthcare).