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You'll build the AI agent capabilities that power Sapien's autonomous finance operations. This means designing novel architectures for reasoning over complex financial data, implementing verifiable and observable agent workflows, and building systems that learn and adapt to each company's unique operations. This is a research-meets-product role. You'll work on cutting-edge agent capabilities—from observability and library learning to semantic search and multi-modal parsing—and ship them directly into production for customers.
Job Responsibility:
Design and implement agent architectures that enable observability, human-in-the-loop verification, and precise context control across complex financial workflows
Build library learning systems that reduce LLM dependencies by learning reusable patterns for planning, code generation, and data localization from customer interactions
Create graph-based company representations and develop efficient search methods using embeddings, semantic clustering, and custom retrieval strategies
Build multi-modal parsers that unify diverse financial data sources (Excel, ERPs, CRMs) into coherent, queryable schemas that agents can reason over
Design benchmarking and evaluation suites that quantify Sapien's accuracy, reliability, and business impact across different customer workflows
Requirements:
Strong algorithmic thinking
Experience with modern agent frameworks, LLMs, and AI systems: fine-tuning, retrieval augmentation, tool use, or agentic architectures
Comfort working end-to-end: from implementing research ideas and prototyping architectures to deploying production systems and iterating on real customer feedback