The Vision: System-Level Optimization

Most current RSI work is highly LLM-centric, treating model weights as the sole unit of improvement. Every step inherits the massive cost of a training run, and compounding progress arrives late. We take a whole-system view: the LLM is just one component of a larger reasoning system that includes code, prompts, search strategies, and tool use. We are building a self-optimizing optimizer—a system where every task it tackles supplies the signal needed to optimize its own orchestration code.

As an AI Engineer, you will build a robust, scalable platform for our intelligence on top of foundation models. You will architect a complete system that surrounds the LLMs, managing the complex, multi-step interactions required to extract and synthesize information. You must be comfortable working in, and building, the high-performance infrastructure that makes our fast, self-improving reasoning possible.

You are a good fit if you:

• Think and breathe Python. You are a Python engineer proficient in building complex, agentic systems or multi-step, stateful execution frameworks.

• Work autonomously to develop both clearly defined and ambiguous ideas, including your own, into reality.

• Excel a