We focus on solving real business problems blending agnostic generative AI with applied AI.

You’ll sit at the engineering core of reliability, owning infrastructure projects, incident response and RCAs, and change requests with ready-to-use runbooks. If you’ve already owned a serious SaaS product and want to scale that discipline to a fleet, step in. Bring expert-level AWS, production-grade coding chops, ruthless scope control, and daily, critical use of AI tools. If you’re ready to keep the lights on, please apply.

What you will be doing

Complex infrastructure migrations, consolidations, production-grade automations, monitoring changes

Triaging production outages, implementing immediate fixes, and writing root cause analyses with permanent fixes assigned to the responsible teams

Creating, reviewing, and executing changes in production, including validating whether a proposed change is safe to execute

What you will NOT be doing

Living in Jira and endless status meetings - we value people who can drive solutions, not just track problems

Maintaining outdated systems indefinitely - you'll be empowered to drive meaningful improvements

Getting blocked by bureaucratic approval chains - you'll have the authority to execute immediate fixes to resolve incidents

Key responsibilities

Build, maintain, and improve CI/CD pipelines to enable fast, safe, and repeatable deployments

Automate repetitive operational tasks by writing scripts and internal tools to improve team efficiency

Deploy and manage microservices on cloud platforms including configuration, scaling, and troubleshooting

Participate in incident response and post-incident reviews; maintain runbooks for critical systems

Improve monitoring and observability through dashboards, alerts, and log pipelines

Write and maintain technical documentation for systems and processes you own

Candidate requirements

3+ years of hands-on DevOps engineering experience in a production environment

Proven experience with Azure; familiarity with AWS or other cloud platforms is a plus

Proficiency in Terraform for infrastructure provisioning and change management

Hands-on experience with CI/CD platforms such as GitHub Actions or Argo Workflows

Experience with Docker, Kubernetes, and container ecosystems (ECS, EKS, or AKS); Helm proficiency required

Solid Linux fundamentals: processes, networking, permissions, and troubleshooting

Familiarity with observability tools such as the LGTM stack, Datadog, or CloudWatch

Competence in Python or Bash scripting

Security-first mindset: IAM least-privilege, secrets management, and container hardening