Without an internal champion, the AI stack you bought is dead in 90 days. Here is the JD, the comp, and the 30-60-90 we hand them.
Almost every AI deployment that died in the first 90 days died for the same reason. Nobody owned it after the implementer left. The fix is a named internal champion. Below: the job description, the comp range, the 30-60-90 plan we hand them. The tradeoffs we made and why Every architecture choice in this category is a tradeoff.
Here are the ones we have made consciously, and the alternative we did not pick. We use Pipecat instead of building our own orchestration. The win is months of saved engineering. The cost is being a release behind on a few model integrations. We use Anthropic as the default LLM with OpenAI failover, not the other way around.
Without an internal champion, the AI stack you bought is dead in 90 days. Here is the JD, the comp, and the 30-60-90 we hand them. It is filed under AI Strategy because that is where operators looking for this problem actually start, and it is written from production work rather than from a content calendar.