Senior AI Engineer, Agentic Data Enrichment

Posted 2 Days Ago
San Francisco, CA, USA
In-Office
230K-340K Annually
Senior level
Fintech • Security • Analytics • Financial Services
Elegantly designed products (KYB, Fraud, Credit). 2,000+ Bank, Lending, and Government Clients.
The Role
Own production LLM-driven agent systems for business data enrichment, including classification, web discovery and verification, entity linking, legitimacy scoring, and risk signals. Build shared agent infrastructure, tools, evaluations, tracing, and cost controls. The role requires production Python engineering, browser automation, multi-provider LLM expertise, structured-output design, web scraping, and evaluation methodology. This is a hybrid role based in San Francisco with four in-office days weekly.
Summary Generated by Built In

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 🔥

Skills Required

  • Shipped LLM-driven agents to production with real users, costs, failure modes, and on-call responsibility
  • Strong async Python experience
  • Experience with structured-data libraries, modern web frameworks, and relational databases
  • Experience with multiple frontier LLM providers and at least one agent framework
  • Deep knowledge of LLM agent failure modes
  • Built or maintained evaluation methodology, including golden datasets, scoring functions, labeling guidelines, and regression diagnostics
  • Browser automation experience, including headless browsers, anti-bot evasion, and authenticated flows
  • Informed opinions on structured-output reliability, including JSON Schema mode, function calling, and text extractors
  • Web scraping at scale, including anti-bot evasion, residential proxies, request fingerprinting, authenticated flows, or CDN defeats
  • Evaluation-framework experience with LangSmith, Braintrust, Evals, or custom systems
  • Entity resolution, record linkage, or fuzzy matching at scale
  • Browser automation experience at the DevTools Protocol level
  • Experience building a tool registry or toolset abstraction across LLM providers
  • Cost and latency optimization experience, including caching, model routing, thinking-budget tuning, or prompt-cache optimization
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Chandler, AZ
21 Employees
Year Founded: 2021

What We Do

Baselayer empowers over 2,000 financial institutions and government agencies to trust the small and medium-sized businesses they serve. We use proprietary machine learning to search government records, the web, and private databases to answer questions about Compliance, Risk, or Fraud about any business in the United States. Our solution suite includes tools for identity verification (Know Your Business), enhanced due diligence, fraud prevention, risk profiling, lien filing, and portfolio monitoring. Our platform also offers unique credit stacking capabilities and an advanced repeat fraud prevention system. Baselayer is integrated into companies with over 30 million accounts, rating and verifying real-time applications. Baselayer.com

Similar Jobs

Gusto Logo Gusto

Marketing Manager

Fintech • HR Tech
Easy Apply
Hybrid
5 Locations
4405 Employees
109K-161K Annually

WorkWhile Logo WorkWhile

Product Manager

Artificial Intelligence • HR Tech • Information Technology • Machine Learning • Software • App development • Industrial
Hybrid
4 Locations
100 Employees
160K-200K Annually
Hybrid
Santa Clara, CA, USA
289097 Employees
Hybrid
2 Locations
289097 Employees

Similar Companies Hiring

Hanover Park Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
42 Employees
Kepler  Thumbnail
Artificial Intelligence • Fintech • Software
New York, New York
9 Employees
Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account