Parasail is redefining AI infrastructure by enabling seamless deployment across distributed GPU networks, optimizing for cost, performance, and flexibility. Our mission is to give AI developers a fast, cost-efficient, scalable cloud experience free from vendor lock-in.
We build the company the same way we build the product. Parasail runs on agents, from kernel optimization through to how we answer questions about our own business, and this role sits close to the center of that.
Role Summary
Every inference request we serve is a decision about hardware, cost, and performance. Making those decisions well, at scale, across a distributed GPU fleet, is a data problem before it is anything else. The intelligence layer behind those decisions is one of Parasail's real advantages, and it is what this role owns.
Our internal analytics are agent-native. Teams ask the business questions directly and get real analysis in minutes,
on data infrastructure designed so that people and agents query it the same way. It is a different way to run a company, and it is a large part of why a small team moves as fast as we do.
You will own and expand that layer. You will design the data models behind fleet and unit economics, build the analytical capabilities the rest of the company runs on, and turn questions that used to take a week into answers that take a minute. Work you ship compounds, because it becomes something the entire team can use immediately.
You will work through MCP connections and agentic tools every day. We expect you to be productive in that stack from week one.
Questions You Will Answer
- What does a token actually cost us across hardware generations and workload profiles, and where does that curve bend?
- Which workloads run best on which hardware, and what is that difference worth to a customer?
- Where is capacity earning, and where is it
📌 Business Intelligence Associate (Las Palmas de Gran Canaria)
🏢 Parasail
📍 Las Palmas de Gran Canaria
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