Staff Software Engineer
Company: David Joseph & Company
Location: New York, NY
Salary: $200,000 - $250,000 a year
Type: Full-time
Posted: 2026-07-20
About this role
New York City, NY · On-site · Full-time
Compensation: $200,000–$250,000 + 0.1%–0.35% equity
### About the Company
A seed-stage, venture-backed startup building an AI operating system for the finance and CFO function — deploying audit-ready AI agents that connect to a company's existing finance stack (ERPs, banks, billing, payroll, CRM, contracts, email) to automate the work behind close, revenue recognition, reporting, cash management, and audit readiness. The company is backed by leading investors and finance operators, with the goal of letting finance teams review exceptions while AI handles the rest.
Founded 2023 · 1–10 people · Industry: AI Tools
### The Role
Own the platform layer that every engineering pod depends on. This is a high-ownership, deeply technical IC role: identify the bottlenecks limiting the company, work directly with engineers, accountants, and customers, and build the abstractions that make hard problems simple. Staff here means depth of impact, not span of control — everyone keeps writing code.
What you'll be doing
- Own the agent harness the entire company builds on — abstractions for context, verification, guardrails, observability, and developer tooling so every pod can ship audit-grade AI agents on shared rails.
- Design and build the financial context graph (ledger state, dimensions, policies, contracts, precedent, entitlements), keeping it coherent, scalable, and multi-tenant safe.
- Define the verification, auditability, evals, and observability standards that determine whether AI output is safe for a customer's books — and enforce them by construction.
- Architect the financial data platform: ingestion, normalization, reconciliation, and the canonical ledger model that turns data from ERPs, banks, billing, payroll, CRMs, and email into a trustworthy source of truth.
- Design the durable execution layer for long-running AI workflows and the exactly-once, audit-ready write-back path to ERPs and systems of r...