Brainco

Brainco

Product Manager, Financial Services

San Francisco Bay Area · Senior

Sponsorship not specifiedDetected 52 days ago
DatabricksAccountingFP&A

Stay score

odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

Personalize to your clock →

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

7 transfer filings in the last year, covering 7 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • Brain Co.'s financial services products run inside large enterprises, asset managers, banks, specialty lenders, and corporate finance teams.
  • You'll set the roadmap, define the standards every deployment is held to, and decide which capabilities become part of the core product.
  • You'll have a point of view on which parts we go after next, and the standing to act on it.

Responsibilities

  • Build rather than specify. Prototype in design or in code. We'd take something working today over a PRD tomorrow.
  • Own the accuracy and control model. These are regulated institutions with almost no tolerance for a wrong number. You decide where an agent acts, where a human reviews, what gets cited back to source, and how the system fails safely.
  • 7+ years building products, with a track record of owning an area end to end: discovery, launch, and the iteration after.
  • Experience shipping into complex, document-heavy environments where being wrong is expensive.
  • Extreme comfort with ambiguity. You structure your own work and don't wait for a playbook.
  • You've built for financial services, accounting, audit, lending, credit, fund reporting, or the office of the CFO, and can talk to a practitioner in their own vocabulary.
  • Brain Co. builds AI-native operating systems for large, regulated institutions.
  • Collaborate with industry veterans from Tesla, DeepMind, Databricks and more
  • If you want to see your work deployed at scale with real impact, Brain Co. is the place to build.

Requirements

  • You can explain a modeling trade-off to an engineer, then the same decision to a CFO.

Compensation

  • Competitive salary

Benefits

  • Medical, Dental, and Vision (100% Coverage)
  • Paid Maternity and Paternity Leave
  • Commuter Benefits
  • Earn competitive compensation + meaningful equity in a high-growth company

Company info

  • Rebuild how the world works, to make institutions work better for the people they serve.
  • ABOUT BRAIN CO.
  • Each system is built for a specific industry, powered by agents that push real workflows forward.
  • Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.
  • Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.
  • Joining now means shaping both the company and a new category of applied AI.
  • Every project here ships to production and is expected to create measurable customer value and impact.
  • You'll work alongside exceptional peers on some of the hardest problems in applied AI.
  • It's the kind of work you'll still be proud of in ten years from now.

This listing is sourced directly from Brainco's careers page and normalized into a canonical job model.