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Exponent

Lead Engineer, AI Accounting

Posted 6 Days Ago
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Hybrid
New York, NY, United States
160K-200K Annually
Senior level
Hybrid
New York, NY, United States
160K-200K Annually
Senior level
Own and evolve the AI Accountant’s full-stack systems, with emphasis on backend architecture, reliable third-party data ingestion, idempotent processing, background jobs, account synchronization, and production operations. Integrate LLMs and ML into classification and reconciliation workflows with strong validation and failure handling. Design PostgreSQL schemas and ensure transactional correctness while shipping frequently and owning systems end to end.
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About Exponent

Exponent is a financial platform built for franchise and multi-location restaurant operators. We offer three integrated products: financing programs including a charge card, acquisition and build-out loans, and an AI-powered Accountant. Operators get one place to manage spend, get growth capital and automate their financial operations. We have secured significant equity and credit capital, and we're backed by leading institutional investors and family offices who run large franchise portfolios.

The role

You'll own core systems in our AI Accountant, built on Ruby on Rails. It pulls in an operator's POS, banking, payroll and processor data, classifies and reconciles it, and automates the monthly close.

This is a full-stack role with a focus on backend architecture. You'll report to our Head of AI Accounting & Engineering, on a small, experienced team that ships to production multiple times a day. It's hands-on IC work, with a path to leading engineers as the team grows.

What you'll do

  • Own systems end to end. Design, build, ship and run systems in production, from schema to UI to deploy to on-call. You own what you build after it goes live.
  • Shape the backend architecture. Make the calls on how the AI Accountant's data, jobs and services fit together as it grows.
  • Make unreliable data reliable. Integrate with difficult third-party APIs. Build ingestion that is idempotent by default (deduplication, safe replay, historical backfill), so any source can be re-pulled and re-processed without corrupting the ledger.
  • Keep every account in sync. Own the background job system that keeps thousands of accounts in sync: scheduling, locking, retries, failure handling, and the monitoring that tells us when a sync quietly stopped. A stuck job is a product bug, not an ops chore.
  • Put LLMs and ML into the product path. Models already do classification and reconciliation in the product, and we're taking it from build to first pilots. That's when the real decisions get made about output validation, confidence thresholds, fallbacks and failure handling. You'll make them, and make a probabilistic component behave inside a system that has to be deterministic where it counts.
  • Help build the company. Small team, broad scope. Every engineer owns what they ship and uses judgment instead of waiting for direction. You'll learn how our technology helps operators move faster and run better.

The ideal candidate

  • You ship fast. You've taken a feature from idea to production in a week. You'd rather ship a small thing this week than a big thing next month.
  • You know when to slow down and focus on the big thing. Ledgers, money movement and anything a customer trusts us with get the time they need.
  • Thoughtful critique makes you better. You ask for review early, take hard feedback well and give it with care.
  • You make the people around you smarter. You share what you know, say "I don't know" without hesitating, and work hard at explaining things clearly.
  • You want to build something new. You'd rather shape a product early than maintain a finished one, and having no playbook appeals to you.
  • Quality is part of every step. Fast means a smaller scope, not rougher work. Tests, error states and the words an operator reads all count from the start.

Requirements

  • 5+ years of engineering, with end-to-end ownership of systems in production
  • Full-stack experience, with depth on the backend
  • Deep experience in a server-side framework: Rails, Django, Phoenix, TypeScript or similar
  • Expertise in AI-assisted development: you use AI tools in your daily work and know where they help and where they don't
  • PostgreSQL: schema design, indexing, transactional correctness
  • Integrating with unreliable third-party APIs: thin docs, no webhooks, surprise format changes, duplicate or partial data
  • Idempotent data ingestion (deduplication, replay, backfill) and background job infrastructure (scheduling, locking, retries, failure handling)

Strongly preferred

  • Fintech experience, or anywhere getting money math right was the job
  • Ruby on Rails experience. It doesn't need to be recent
  • POS or restaurant data: Square, Toast, Qu, Revel, delivery platform payouts, processor settlement files
  • Accounting platforms: QuickBooks Online, Sage Intacct, NetSuite, Restaurant365
  • Financial data aggregators: Plaid, Rutter, Stripe

Nice to have

  • Production LLM experience: LLMs in a product path, including output validation and failure handling
  • Ledger, double-entry or reconciliation system design
  • Classification models with measurable evaluation
  • CSV and file-based import pipelines at scale

The details

  • $160,000–$200,000 base salary, commensurate with experience, plus equity
  • Hybrid, based at our Flatiron office in New York: at least 2 days a week in the office, 3+ preferred. Commuting in from NJ, Westchester, Connecticut, Long Island or Philly works.
  • Benefits: PTO, healthcare, HSA/FSA, 401(k)

How to apply

Email [email protected] with a short note on why this role interests you.

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