AI for account management and revenue growth. Backed by Y Combinator.
About the role
We’re building a replayable environment engine over real enterprise history. The system reconstructs a company’s context as it existed at any past time, then exposes that state through the same tools an agent would use in production. This lets us place new policies and agent configurations inside real historical environments, observe how they reason and act, and grade their performance against real outcomes.
More about this role
Ambral Labs helps enterprises own the intelligence behind their most important workflows.
Every company has years of historical evidence showing how work gets done: the context people had, the decisions they made, the actions they took, and the outcomes that followed. Today, most of that history is inert. It isn’t structured in a way that companies can use to evaluate models and improve agent behavior.
Ambral turns this history into replayable environments and eval sets grounded in real workflows and observed outcomes. We use those environments to improve model performance through reinforcement learning and other post-training techniques, alongside context engineering, harness design, and agent engineering.
The result is better, more cost-efficient AI for each enterprise’s specific work, powered by open-weight models that the company can own and control rather than permanently renting from a model provider.
We're YC S2025 , have raised millions in funding, and are already deployed inside multi-billion dollar enterprises. Now we're growing the founding team.
We’re building a replayable environment engine over real enterprise history.
The system reconstructs a company’s context as...
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