Staff Software Engineer, Data Infrastructure

Build ingestion that accepts events from millions of Lovable apps, treats every producer as untrusted, and keeps one tenant's bad traffic from slowing or corrupting another's data.

Build managed analytical storage for every user, including schema management, partitioning, and compaction of a constant stream of small writes.

Make queries fast when you can't keep compute warm for every tenant.

Build the runtime for agent-written connectors: isolated execution, credentials, scheduling, retries and state.

Make cost per tenant measurable, then drive it down, through metering, limits and workload isolation.

Expose data, metadata and tools to the Lovable agent so it can build software on customers' data.

Run what you build, including observability, freshness and recovery.

An infrastructure engineer who has built and run data systems in production at scale, and wants the harder version of the problem: millions of tiny tenants on shared infrastructure.

Deep experience in at least one layer (ingestion, storage formats and table layout, query execution, or orchestration), and the range to work across the others.

Experience with multi-tenant or untrusted workloads: isolation, noisy neighbours, and keeping cost per tenant low.

Good judgment on calls no one can check for you: the right abstraction, the tradeoff between cost and latency, whether a design holds at 10x.

You work with AI agents end to end. Your output is the systems you build, not the code you type by hand.

You ship, and you own what you ship in production.