Build observability, automation, and AIOps foundations. Focus on deliverable output, reusable assets, and support-driven product improvement.

• Use logs/metrics/traces to understand issues; complete a dashboard + alert + runbook for one service.
• Turn support pain points into product improvements (copy, self-service, workflow).
• Understand MLOps/AIOps basics: deployment, rollback, drift monitoring.
• Build or extend an agent skill for automation or support.

Responsibilities

• Observability & Automation – Set up dashboards/alerts; script repetitive ticket steps.
• RCA & Support Insights – Participate in RCAs; log user pain points weekly; propose product fixes.
• Agent & Skill Prototyping – Build a lightweight agent (e.g., telegram bot) with at least one reusable skill (log fetch, health check, etc.).
• ITSM / Tools (optional) – Optimize a small workflow in incident management tooling.
  

Requirements

• Must-have
• CS/Data/AI or related major; Linux + scripting (Shell/Python); basic SQL.
• Good documentation – write actionable runbooks.
• Empathy & product thinking – improve user experience from support data.
• Basic understanding of agents and skills. Nice-to-have
• K8s, CI/CD, Terraform.
• MLOps project experience.
• Built a simple LLM agent or defined skills (LangChain, function calling).
• TSM tool experience.