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- Maintaining outdated systems indefinitely - you'll be empowered to drive meaningful improvements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