DevOps Engineer

Black Book is looking for a Mid-to-Senior Dev Ops Engineer with a minimum of 3 years' experience in Dev Ops and Cloud Infrastructure Operations to help build, automate, and operate the CI/CD and cloud platforms that support our automotive data and technology products.

As part of the Hearst Transportation group, Black Book combines automotive expertise, data science, predictive analytics, APIs, and modern cloud technology to help dealerships, lenders, OEMs, insurers, fleet operators, and other automotive businesses make better decisions.

You'll work closely with software engineers, data engineers, data scientists, and analysts to improve how applications and infrastructure are built, deployed, monitored, and supported.

This is not a ticket-driven infrastructure role. We're looking for an engineer who enjoys automation, troubleshooting complex problems, improving platforms, and taking ownership from idea through production.

Our environment includes:

AWS Kubernetes/EKS Pulumi Argo CD Azure Dev Ops Python Power Shell Bash Linux Windows Grafana AI Engineering Tools

You don't need experience with every tool. Strong engineering fundamentals, curiosity, and the ability to learn matter more than matching our stack exactly.

• Build and operate highly available AWS and Kubernetes infrastructure.
• Develop and maintain Infrastructure as Code and automation.
• Improve CI/CD and Git Ops workflows.
• Automate operational tasks with Python, Power Shell, Bash, or similar tools.
• Troubleshoot production issues across applications, containers, networking, and cloud infrastructure.
• Improve observability, reliability, security, performance, and cost efficiency.
• Partner with development and data teams to promote Dev Ops and shift-left practices.
• Participate in incident response and help eliminate root causes.
• Document solutions, share knowledge, and mentor teammates.
• Support customer-impacting issues when needed.

We expect our engineers to be highly effective with modern AI development and engineering tools.

That means going beyond basic prompting or code completion. You should be comfortable using tools such as Claude Code and similar AI agents to accelerate development, troubleshooting, automation, documentation, and research.

We value engineers who can:

• Give agents clear context, constraints, and acceptance criteria.
• Build reusable skills, hooks, instructions, and workflows
  .
• Connect agents to appropriate tools, repositories, APIs, and documentation.
• Use automated validation and guardrails around agent-driven work.
• Critically review AI-generated code, infrastructure, and recommendations.
• Understand the security implications of agent access and permissions.
• Recognize when AI is the right tool - and when it isn't.

We view AI as an engineering multiplier, not a substitute for engineering judgment.

• Experience building or supporting production cloud infrastructure.
• Strong AWS knowledge or experience with another major cloud provider.
• Experience with Infrastructure as Code such as Pulumi, Terraform, Cloud Formation, or Ansible.
• Experience with Docker and Kubernetes.
• Experience building or maintaining CI/CD pipelines.
• Ability to automate using Python, Power Shell, Bash, or another programming language.
• Experience with Linux and/or Windows environments.
• Strong troubleshooting and problem-solving skills.
• Understanding of CI/CD, automation, and shift-left engineering practices.
• Ability to work independently while collaborating effectively with others.
• Strong communication, ownership, and technical judgment.

Experience with any of the following is helpful, but not required:
Kubernetes/EKS, Helm, Argo CD, Datadog, Grafana, Prometheus, networking and DNS, REST or GraphQL APIs, .NET, Node.js, Python development, Dev Sec Ops , SRE practices, MCP servers, or AI agent/tool integrations.

We value engineers who:

• Shift left and automate recurring problems.
• Own outcomes
  , not just assigned tasks.
• Keep learning and adapt as technology changes.
• Embrace ambiguity and work through unfamiliar problems.
• Choose simplicity over unnecessary complexity.
• Use AI effectively while validating its work.
• Think about the customer and the reliability of the systems they depend on.
• Share knowledge and help the team improve.

Black Book offers the scale and stability of Hearst while giving engineers the opportunity to work across modern cloud, Kubernetes, automation, data, and AI technologies.

Benefits include comprehensive health coverage, 401(k) with…