Senior AI Engineer, Agentic Data Enrichment
Baselayer · San Francisco, California
About this role
**ABOUT BASELAYER** Every business in America needs a bank account to exist. The system that decides whether they’re real, who’s behind them, and whether they’re a risk runs on infrastructure from the 1980s. Baselayer is rebuilding that layer from scratch. Baselayer is the identity layer for institutions across the United States—building the most complete business graph in America and connecting every human tied to it. We fuse public records, IRS data, sanctions lists, web signals, and fraud telemetry from 2,200+ financial institutions into a single graph that resolves any business and the humans behind it in milliseconds. Trusted by 20%+ of financial institutions in America (including FIS, Rho, Socure, and leading loan infrastructure providers). The graph is becoming infrastructure for anyone who needs to know if a business is real and worth trusting: gig platforms, marketplaces, AI companies, and commerce infrastructure at scale. --- **ABOUT THE TEAM** We solve real-time entity resolution at a scale no one else has cracked—fusing dozens of data sources into a single business identity graph and resolving entities in milliseconds. It’s a graph AI problem, a retrieval problem, and a fraud-modeling problem stacked together. You’ll join a small team with real ownership and velocity—no layer of process between an idea and shipping it. --- **ABOUT THE ROLE** Baselayer answers questions the loan application didn’t ask. For every business that crosses our queues, we need to know what the business actually does, where it actually lives on the web, whether the people it names match public record, and whether anything across the open web contradicts the story we were told. We do this with **LLM-driven agents** that crawl, click, search, and extract structured evidence from across the web—treated as a **production data pipeline**, not a research demo. We’re hiring a **Senior AI Engineer** to own a slice of this enrichment surface end-to-end. --- **WHAT YOU’LL DO** - Own industry/category classification of businesses from heterogeneous signals (name, website, directory presence, reviews). - Build and maintain discovery and verification systems for a business’s real web presence (filtering aggregators, parked domains, brand collisions, and impersonators). - Link individuals to businesses via public web evidence (e.g., confirming a named officer/employee genuinely works there). - Develop risk/legitimacy scoring derived from web-presence signals, fed back into downstream underwriting. - Build and evolve shared agent infrastructure: provider-agnostic base agents, shared toolset registry (browser navigation, search, scraping, structured database lookups, scoring), eval harness, and instrumentation for token-and-tool tracing. - Own model selection, agent design, prompt/tool engineering, eval methodology, and cost control across your enrichment surface. --- **MINIMUM REQUIREMENTS** - Shipped **LLM-driven agents to production** (not notebooks/demos). Real users, real cost, real failure modes, real on-call. - Strong **async Python**, including structured-data libraries, modern web frameworks, and relational databases. - Experience across multiple frontier LLM providers and at least one agent framework, with deep knowledge of failure modes. - Built/maintained eval methodology (curated golden datasets, scoring functions, labeling guidelines, regression diagnostics). - Browser automation experience: headless browsers, anti-bot evasion, authenticat
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