---
title: 'Senior AI Engineer, Agentic Data Enrichment at Baselayer'
canonical: 'https://feeny.ai/job/senior-ai-engineer-agentic-data-enrichment-baselayer-san-francisco-6d49wszme7f9'
type: 'job'
last_seen: '2026-09-06'
---

# Senior AI Engineer, Agentic Data Enrichment at Baselayer

- **Company:** Baselayer
- **Location:** San Francisco, CA
- **Posted:** 2026-09-01
- **Last confirmed live:** 2026-09-06
- **Apply:** https://job-boards.greenhouse.io/baselayer/jobs/5412419008

## 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 latency, and expanding the identity layer beyond finance into every platform that needs to trust a business.

If you want to work on something foundational — the kind of infrastructure that gets built once and everything else runs on top of — this is it.

## ABOUT THE ROLE

Baselayer answers questions the loan application didn't ask. For every business that crosses our queues, we need to know things that aren't on the form: what the business actually does, where it actually lives on the web, whether the people it names match the public record, and whether anything across the open web contradicts the story we were told. We answer those questions with LLM-driven agents that crawl, click, search, and extract structured evidence from across the web - and we treat this 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 or employee genuinely works there).
- Develop risk/legitimacy scoring derived from web-presence signals, fed back into downstream underwriting.
- Build and evolve the shared agent infrastructure: provider-agnostic base agents, shared toolset registry (browser navigation, search, scraping, structured database lookups, scoring), eval harness, and instrumentation surface for token-and-tool tracing.
- Own model selection, agent design, prompt and tool engineering, eval methodology, and cost control across your enrichment surface.

## MINIMUM REQUIREMENTS

- Shipped LLM-driven agents to production - not notebooks, not 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 or maintained eval methodology: curated golden datasets, scoring functions, labelling guidelines, regression diagnostics.
- Browser automation experience: headless browsers, anti-bot evasion, authenticated flows.
- Holds informed opinions on structured-output reliability - when to use JSON-schema mode vs. function calling vs. extractor-on-top-of-text.

## WHAT SETS YOU APART

- Web scraping at scale: anti-bot evasion, residential proxies, request fingerprinting, authenticated flows, CDN defeats.
- Eval-framework experience (e.g., LangSmith, Braintrust, Evals, or custom).
- Entity resolution / record linkage / fuzzy matching at scale.
- Browser-automation experience at the devtools-protocol level.
- Built a tool registry or toolset abstraction over multiple LLM providers.
- Cost/latency optimization: response caching, semantic caching, model routing (cheap-first then escalate), thinking-budget tuning, prompt-cache hit-rate work.

## WORK LOCATION

- Based in SF; hybrid - 4 days per week in office.

## COMPENSATION

- Salary Range: $230,000 – $340,000 + Equity

## BENEFITS

- Time off when you need it: Flexible PTO so you can recharge without red tape.
- In-person energy: We're based in SF and meet in the office 4 days a week.
- Competitive compensation: We pay well and back it with equity. We want you to think and act like an owner.
- Career rocket fuel: You'll help build the foundation of a high-growth startup, working side by side with experienced founders and team members who've done it before.
- Benefits on us: We cover 100% of your health, dental, and vision premiums. No surprise deductions from your paycheck.
- 401(k) with company match: We match your contributions so your future self benefits too
- HSA contributions included: We contribute to your HSA on applicable plans, so your coverage works as hard as you do
- Stay healthy, stay sharp: A $250 monthly gym stipend to help you bring your best self to work, and everywhere else
- A seat at the table: We believe in transparency, radical candor, and giving every team member a voice 🔥

## About Baselayer

## Company Overview
- **One-liner**: AI-powered platform for business identity verification, fraud detection, and risk scoring, serving 2,200+ financial institutions and government agencies.
- **Entity Type**: Private (Seed stage – raised $6.5M seed round in May 2024)
- **Headquarters**: New York, NY, USA
- **Founded**: ~2024 (inferred from seed round announcement)
- **Founders**: Timothy Hyde (CEO) and Jonathan Awad (CTO)

## Core Business
- **Primary industry**: Financial technology (FinTech) – business risk intelligence, identity verification, compliance, fraud prevention.
- **Target customers**: B2B – banks, fintechs, credit unions, government agencies, B2B platforms; end-users are small and medium-sized businesses.
- **Mission**: To make financial services more accessible to small businesses by providing real-time trust and risk infrastructure.

## Products & Services
- **Business Verification (KYB)**: Instantly verifies business identity, officers, owners, sanctions, legal and military risk using public records and AI.
- **Fraud Prevention**: AI-driven fraud detection with a consortium network to identify repeated fraud and emerging trends.
- **KYB Rating**: Proprietary AI score combining all available signals for intelligent decisioning.
- **Industry Prediction**: Automated business classification using signals from 120M+ business records.
- **Portfolio Monitoring**: Continuous, configurable monitoring of sanctions, fraud, adverse events, and entity changes.
- **Lien Searching & Filing**: Accelerated search and filing of liens against businesses.
- **Website & Social Media Analysis**: AI agents assess online presence and social/review data for risk signals.
- **Risk Rating**: Graded industry prediction scores via proprietary clustering and multi-source data.
- **Credit Stacking**: Unique capability to detect credit stacking risk (multiple applications).

All delivered via a unified API and web dashboard (Risk Co.Pilot) with pre-built integrations.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Total Funding**: $6.5M seed round (May 2024, from 7 undisclosed investors).
- **Annual Revenue**: Estimated $25M–$50M (LinkedIn data).
- **Key Metric**: Trusted by 2,200+ financial institutions; platform integrated into companies with 30M+ accounts.
- **Notable Investors/Partners**: Investors not named in available sources; partners include "ure" (likely a branding/media partner) per a 2025 PR Newswire announcement.
- **Growth Signals**: LinkedIn followers grew 1,840% year-over-year to ~23,600; 16 active job postings across engineering, sales, customer success, and operations. Headcount decreased 32.4% yearly (possibly restructuring after seed raise). Partnerships and product expansions ongoing.

## Competitive Advantages
- **AI-native architecture**: Combines public records, proprietary AI agents, and networked consortium intelligence for real-time, explainable risk decisions.
- **Broad data coverage**: Access to government records, web data, private databases, and a fraud consortium network.
- **High auto-approval rates**: Claims 92% increase in auto-approval rates for clients.
- **Agentic AI**: Automates manual risk checks, reducing cost and human error (Risk Co.Pilot).
- **Network effects**: Consortium model surfaces emerging fraud trends across participants, creating a moat.

## Strategic Focus
- Deepening AI capabilities (agentic AI, predictive modeling) to automate compliance and fraud workflows.
- Expanding partnerships with financial institutions and government agencies.
- Growing the fraud consortium to increase network value.
- Scaling platform usage beyond KYB into ongoing monitoring, lien services, and credit risk.

## Why Work Here
- **Culture**: Described as fast-paced, ambitious, and collaborative – "ideas over titles," "win together," "pace with purpose." The careers page emphasizes "cracked" individuals, founder mindset, and high ownership. Ego is not tolerated.
- **Work Environment**: Offices in New York (HQ), San Francisco, and Arizona (Mesa/Chandler). Likely hybrid/onsite given the roles posted; remote flexibility not explicitly stated.
- **Benefits**: 401(k) with matching, top-tier medical/dental/vision, unlimited PTO, competitive salary.
- **Engineering Culture**: Heavy focus on AI, machine learning, data engineering. Teams are small (≈28 employees), offering outsized impact. Roles include senior AI engineers, identity graph specialists, backend and full-stack engineers.
- **Employee Sentiment**: Glassdoor rating 3.6/5 (19 reviews). Strengths: compensation (3.8). Weaknesses: culture (2.8) and career growth (2.8) – typical for early-stage intense environments. Work-life balance rated 3.4.
- **Ideal Candidate**: Self-starters who want to be future founders, thrive in ambiguity, and are "wildly cracked" – bring high ambition and low ego.

## Sources
1. [baselayer.com](https://baselayer.com/) – Company website, product descriptions, claims
2. [baselayer.com/about](https://baselayer.com/about/) – Team, mission, culture, benefits
3. [linkedin.com/company/baselayer](https://www.linkedin.com/company/baselayer) – Employee data, revenue estimate, news, ratings
4. [job-boards.greenhouse.io/baselayer](https://job-boards.greenhouse.io/baselayer) – Open roles, hiring philosophy, company description

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