Baselayer

Financial Services

SeniorAIEngineer

$195–300k San Francisco, California, United States Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior AI Engineer at Baselayer. Skills: LLM-driven agents, Agent infrastructure, Web scraping, Entity resolution. Own industry/category classification. Build discovery systems”

Industry & Context.

Financial Services
Problems you'll solve

Root cause analysis

Eligibility Requirements

4 days per week in office

What They're Looking For.

Must Have

Shipped LLM-driven agents to production, async Python, modern web frameworks, relational databases, Experience across multiple frontier LLM providers, at least one agent framework, Built or maintained eval methodology, Browser automation experience, informed opinions on structured-output reliability

Nice to Have

Web scraping at scale, Eval-framework experience, Entity resolution at scale, record linkage at scale, fuzzy matching at scale, Browser-automation experience at devtools-protocol level, Built a tool registry, toolset abstraction over multiple LLM providers, Cost/latency optimization, response caching, semantic caching, model routing, thinking-budget tuning, prompt-cache hit-rate work

What You'll Do.

Own industry/category classification

Build discovery systems

Maintain verification systems

Link individuals to businesses

Develop risk/legitimacy scoring

Build shared agent infrastructure

Own prompt engineering

Full Job Description

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. We're rebuilding that layer from scratch. Baselayer is the identity layer for institutions across the United States — the most complete business graph in America and 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. The legacy credit bureaus took 50 years to build something that gets 60% match rates. We've built something that gets 98% in under two years. Today we're trusted by over 20% of financial institutions in America — including FIS, Rho, Socure and leading loan infrastructure providers. But 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. Trust is the substrate of every financial transaction. We're rebuilding it. ABOUT THE TEAM We're solving 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 any entity in milliseconds. It's a graph AI problem, a retrieval problem, and a fraud-modeling problem stacked on top of each other. The technical depth is real. You'd be joining a small team where the data moat is defensible, the research problems are open, and the infrastructure you build becomes load-bearing for businesses. Ownership is real. Velocity is real. There's no layer of process between an idea and shipping it. We're at an inflection point — the graph is built, the match rates speak for themselves, and the hardest problems are still ahead: graph embeddings, fraud propagation models across the business network, real-time traversal at sub-100ms latenc

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