About the role
We’re hiring an Applied AI Engineer to build the core agent systems powering autonomous financial audits. This is a high-ownership, high-impact role working directly on frontier problems in AI, specifically enabling agents to reason over complex, unstructured, real-world data (PDFs, Excel, images, documents).
You’ll own problems end-to-end, from defining system architecture to deploying production systems that operate reliably at scale. We’re looking for someone with exceptional engineering ability, deep experience building AI agents, and a strong bias for speed and ownership.
What You’ll Do
- Design and build state-of-the-art AI agent systems (planning, memory, tool use, recovery) that operate on messy, out-of-distribution data
- Define and implement agent architectures and experimentation frameworks to continuously improve performance and reasoning quality
- Build fault-tolerant, production-grade systems that integrate seamlessly with the broader platform
- Architect and optimize pipelines that process 100GB+ of heterogeneous data efficiently across distributed systems
- Debug complex agent failures, edge cases, and performance bottlenecks in real-world environments
- Rapidly learn new audit workflows and ship improvements in hours to days, not weeks
What We’re Looking For
- Exceptional engineering talent with a track record of rapid growth and high ownership
- Deep experience building or working with AI agents in production environments
- Strong systems intuition across backend / distributed systems / data processing
- Comfortable operating in fast-paced, ambiguous environments with high expectations and autonomy
- Bonus: experience with agent frameworks, open source contributions, or applied AI research
