Data Infrastructure Engineer

📋 Description

• Build ingestion that accepts events from millions of Lovable apps, treats every producer as
• Build managed analytical storage for every user, including schema management, partitioning, and
• Make queries fast when you can't keep compute warm for every tenant.
• Build the runtime for agent-written connectors: isolated execution, credentials, scheduling
• Make cost per tenant measurable, then drive it down, through metering, limits and workload
• Expose data, metadata and tools to the Lovable agent so it can build software on customers' data.

🎯 Requirements

• An infrastructure engineer who has built and run data systems in production at scale, and wants the
• Deep experience in at least one layer (ingestion, storage formats and table layout, query
• Experience with multi-tenant or untrusted workloads: isolation, noisy neighbours, and keeping cost
• Good judgment on calls no one can check for you: the right abstraction, the tradeoff between cost
• You work with AI agents end to end. Your output is the systems you build, not the code you type by
• You ship, and you own what you ship in production.