Ventajas
Colleagues were friendly, helpful, and supportive.
Desventajas
All the tasks I handled were data engineering–related, and I did not get any (even a single) AI-related task. I even communicated with my manager and requested AI tasks. While he agreed, I continued to receive only data engineering tasks. He explained that “AI is about data—how you get and preprocess it,” which I understand. But in practice, after preprocessing the data, the process stopped there without moving further into AI-related tasks such as RAG or building AI agents.
I was also advised to ask only “high-level” questions to my manager and direct other questions to colleagues, this made learning more challenging. I prefer to learn independently, and although I spent weekends upskilling myself, the expectation of "kacau" colleagues outside working hours felt uncomfortable. Unfortunately, the frequency of “kacau” that out of working hour seemed to be used as part of performance evaluation. Eventually, I was told that I am “not putting enough effort” and was terminated. No KPIs or performance expectations were communicated during the probation period, yet I was informed that I had failed probation.
Overall, while I appreciate the opportunity and exposure, I felt there was a mismatch between the role title (AIOps Engineer) and the actual work assigned (all data engineering tasks).