• Technical founding team with relevant industry experience (part of Nvidia Inception Program)
• Backed by well-known European VCs (SpeedInvest + Galion.exe)
• Building anomaly detection and agentic evaluation on top of AI agent observability stack (Otel Native)
Ideal candidate:
Experience in open telemetry and observability. Preferably in a cloud native startup environment and excited to help product teams achieve maximum developer velocity with best-in-class DX and dev tooling. Bonus if you are an ex-founder.
I would add that "extremely sound data engineering" is also necessary to make observability cost-effective. Some of these otel platforms can burn 10%-25% of your cloud budget to show you your logs. That is insane.
• Previous experience at start-up building tech at scale
• Thinks in terms of product functionality and customer demands not just features
• Familiar with API first practices and frameworks
• Bonus points if you are an ex-founder or have been first hire before
Moyai is an AI-powered agent monitoring tool for AI engineers looking to catch agent failures in production. Reach out to the founder directly: https://www.linkedin.com/in/rhommes/ or visit our website https://moyai.ai
*No agencies or recruiters, and we are unable to provide visa sponsorship
"Because there’s too much you need to feed into it" - what does the author mean by this? If it is the amount of data, then I would say sampling needs to be implemented. If that's the extent of the information required from the agent builder, I agree that an LLM-as-a-judge e2e eval setup is necessary.
In general, a more generic eval setup is needed, with minimal requirements from AI engineers, if we want to move forward from Vibe's reliability engineering practices as a sector.
Just another example of money scaling your way out of a problem. What you don't understand is hard to optimize. Like how you have solved this by acting as an smart router in between that first understands what to optimize and then actually implement that optimization.
My personal opinion is that true engineering, which revolves around turning complex theory into working practice, has seen a decline in grace. Why spend a lot of time trying to master the art of engineering if you can ride the wave of engineering services and get away with it?
In true hacker spirit, I don't think trying to train a model on a wonky GPU is something that needs an ROI for the individual engineer. It's something they do because they yearn to acquire knowledge.
About the company:
• Technical founding team with relevant industry experience (part of Nvidia Inception Program)
• Backed by well-known European VCs (SpeedInvest + Galion.exe)
• Building anomaly detection and agentic evaluation on top of AI agent observability stack (Otel Native)
Ideal candidate:
Experience in open telemetry and observability. Preferably in a cloud native startup environment and excited to help product teams achieve maximum developer velocity with best-in-class DX and dev tooling. Bonus if you are an ex-founder.
Reach out to the founder directly: https://www.linkedin.com/in/rhommes/ or visit our website https://moyai.ai
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