Azure DevOps Engineer

We are dedicated to solving real business challenges by combining agnostic generative AI with applied AI technologies. As a core member of our engineering team focused on reliability, you will take ownership of critical infrastructure projects, incident response, root cause analyses, and change management using ready-to-use runbooks. If you have experience managing a serious SaaS product and are eager to scale that expertise across a broader system, this role offers the opportunity to apply your expert-level AWS skills, production-grade coding abilities, and strong scope management. Daily use of AI tools will be integral to your work. If you are committed to maintaining system stability and driving continuous improvement, we encourage you to apply.

Key Responsibilities

- Lead complex infrastructure migrations, consolidations, and implement production-grade automation and monitoring enhancements.
- Manage triage of production outages by applying immediate fixes and conducting thorough root cause analyses, ensuring permanent solutions are assigned to the appropriate teams.
- Create, review, and execute production changes with a focus on validating the safety and impact of each modification.
- Build, maintain, and optimize CI/CD pipelines to support fast, safe, and repeatable deployments.
- Automate repetitive operational tasks through scripting and development of internal tools to enhance team productivity.
- Deploy and manage microservices on cloud platforms, handling configuration, scaling, and troubleshooting.
- Participate actively in incident response and post-incident reviews, maintaining detailed runbooks for critical systems.
- Enhance monitoring and observability by developing dashboards, alerts, and log pipelines.
- Produce and update comprehensive technical documentation for all systems and processes under your ownership.

Required Qualifications

- Minimum of 3 years of hands-on DevOps engineering experience in a production environment.
- Proven expertise with Azure cloud services; familiarity with AWS or other cloud platforms is advantageous.
- Strong proficiency in Terraform for infrastructure provisioning and change management.
- Experience working with CI/CD platforms such as GitHub Actions or Argo Workflows.
- Solid knowledge of container technologies including Docker and Kubernetes ecosystems (ECS, EKS, or AKS), with proficiency in Helm.
- Strong Linux fundamentals covering processes, networking, permissions, and troubleshooting.
- Familiarity with observability tools like the LGTM stack, Datadog, or CloudWatch.
- Competence in scripting languages such as Python or Bash.
- Security-first mindset with experience in IAM least-privilege principles, secrets management, and container hardening.

Preferred Qualifications and Benefits

While not explicitly listed, candidates who demonstrate a proactive approach to driving meaningful improvements without being hindered by bureaucratic processes will thrive in this role. The position emphasizes autonomy, empowering you to execute immediate fixes during incidents and avoid excessive administrative overhead such as prolonged Jira tracking or unnecessary meetings. This environment is ideal for professionals who prefer solution-driven work and continuous system enhancement.

If you are passionate about maintaining high system reliability and eager to work at the intersection of AI and cloud infrastructure, this opportunity offers a challenging and rewarding career path.