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