AI Engineer

About the Company

We’re building the AI operating system for the CFO office — connecting to a company’s existing finance stack and automating the work behind the close, revenue recognition, reporting, cash management, and audit readiness. Rather than helping accountants write better prompts, our audit-ready agents reason over financial data, explain their decisions, elevate uncertainty, and continuously improve, so finance teams can review exceptions while the AI does the rest.

We’re a well-funded seed-stage team backed by a leading venture firm and a group of prominent AI and finance operators.

Founded 2023
· 1–10 people
· Industry: AI Tools / Fintech

We’re hiring a Staff AI Engineer to own the platform layer that every engineering pod builds on — from agent frameworks and context systems to orchestration, verification, observability, and data infrastructure. This isn’t a module-ownership role; your work multiplies the output of the entire engineering team, and you’ll identify the bottlenecks limiting the company rather than wait for specs from a PM or an architecture committee.

• Own the agent harness the entire company builds on — abstractions for context, verification, guardrails, observability, and developer tooling so every pod ships audit-grade AI agents on shared rails.
• Design and build the financial context graph: the structured layer every agent reasons over (ledger state, policies, contracts, precedent, entitlements) kept coherent, scalable, and multi-tenant safe.
• Define the verification, auditability, evals, and observability standards that decide whether AI output is safe enough for a customer’s books — and enforce them by construction.
• Own the ingestion, normalization, reconciliation, and canonical ledger model that turns ERP, bank, billing, payroll, CRM, and email data into a trustworthy source of truth.
• Design the durable execution layer for long-running AI workflows and the exactly-once, audit-ready path that safely writes back to ERPs and systems of record.
• Build architectural primitives and frameworks that become the foundation other engineers depend on.

Tech stack: Python (primary), agent frameworks, distributed systems, workflow/transactional engines, data infrastructure.

• 2 or more years of agentic AI work, research-oriented background
• 8 or more years software engineering, distributed systems or platform depth
• Platform-layer experience, multiplied output across engineering teams
• Early-stage startup experience, pre-seed through Series B
• NYC in-person
• Startup hours, 6 days a week, 9am to 7pm or 8pm

• Deep agentic AI experience with architectural ownership
• Research-oriented ML or NLP background applied to production
• Prior Staff or Principal IC at a high-growth startup
• Finance, ERP, audit, or compliance domain background

• Frontend-heavy profile without meaningful backend or systems depth
• Tool-list resume without substantive project or architectural detail
• Several short job stints without clear context
• Needs a defined scope or structured environment to operate

• Own the platform layer every engineering pod depends on — org-wide leverage rather than a single module.
• Well-funded seed-stage team with strong venture backing and prominent AI and finance operators behind it.
• Define the abstractions and verification standards for audit-grade AI in finance from the ground up.

• Location — New York City, NY
• Work policy — In-person at the NYC office; startup hours, 6 days a week, 9am–7pm/8pm
• Compensation — $200,000–$250,000 + 0.1%–0.35% equity
• Visa sponsorship — None Available
• Employment type — Full-time