---
title: 'Applied AI Engineer at Sapien'
canonical: 'https://feeny.ai/job/applied-ai-engineer-sapien-new-york-hk9j49nn33bt'
type: 'job'
last_seen: '2026-10-15'
---

# Applied AI Engineer at Sapien

- **Company:** Sapien
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2024-12-16
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/sapien/b31a944b-075f-4302-834f-f949cd3db267

## Job description

## Who we are

Sapien is the engine behind the world’s most important companies. We build agents that learn how a business works from its financial and operational data: its language, operations, and economics. That understanding helps people find opportunities, make better decisions, and act. We work with complex businesses, from manufacturers and restaurant groups to the Fortune 500. Teams at companies including Bayer, Cooper Standard, Blink Charging, Carlex, and Odeko use Sapien to understand their businesses and improve how they run. Our ambition is to build the self-optimizing company by making its people and systems dramatically more capable. We’re headquartered by Madison Square Park in NYC, with $15M+ raised and backing from General Catalyst, Neo, and operators from OpenAI, Google, Microsoft, Ramp, and Stripe. We’re bringing together AI researchers, engineers, and operators to build intelligence for the people who build everything else.

## The role

You'll build the AI agent capabilities that power Sapien's financial and operational intelligence. This means designing novel architectures for reasoning over complex financial and operational data, implementing verifiable and observable agent workflows, and building systems that learn and adapt to each company's unique operations. This is a research-meets-product role. You'll work on cutting-edge agent capabilities—from observability and library learning to semantic search and multi-modal parsing—and ship them directly into production for customers.

## What you'll do

- Design and implement agent architectures that enable observability, human-in-the-loop verification, and precise context control across complex financial and operational workflows.
- Build library learning systems that reduce LLM dependencies by learning reusable patterns for planning, code generation, and data localization from customer interactions.
- Create graph-based company representations and develop efficient search methods using embeddings, semantic clustering, and custom retrieval strategies.
- Build multi-modal parsers that unify diverse financial and operational data sources (Excel, ERPs, CRMs) into coherent, queryable schemas that agents can reason over.
- Design benchmarking and evaluation suites that quantify Sapien's accuracy, reliability, and business impact across different customer workflows.

## What we're looking for

- Strong algorithmic thinking. Demonstrated through ML research, competitive programming, mathematics, or building novel systems from scratch.
- Experience with modern agent frameworks, LLMs, and AI systems: fine-tuning, retrieval augmentation, tool use, or agentic architectures.
- Comfort working end-to-end: from implementing research ideas and prototyping architectures to deploying production systems and iterating on real customer feedback.

## How you work (values we care about)

- Adaptability: You thrive on diverse, open-ended problems. One day you're implementing a new agent architecture, the next you're debugging a customer data issue—and you bring the same intensity to both.
- Ownership: You take problems from research paper to production. You don't wait for direction—you identify what needs to happen and drive it to completion.
- Opinionated: You have strong technical perspectives on what works and what doesn't. You push back on approaches you disagree with and make the team's thinking sharper.
- Mission-driven: You're energized by building AI that transforms how businesses run. You connect technical decisions to real customer outcomes and care deeply about the impact.
- Collaborative excellence: You share knowledge, give thoughtful feedback, and invest in making the team better. You bring new ideas from papers and discussions to elevate everyone's thinking.

## About Sapien

## Company Overview
- **One-liner**: Sapien builds an AI-native platform for financial and operational analysis that connects to live ERP and warehouse data to deliver autonomous, traceable insights for finance and operations teams.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: New York City, New York, United States
- **Founded**: 2024
- **Founders**: Ron Nachum (CEO), Pranav Ravella (CTO), Arya Grayeli (Chief Scientist)

## Core Business
- Primary industry: AI-powered Financial & Operational Analytics / Enterprise Software
- Target customers: Mid-market to Fortune 500 companies; FP&A, strategic finance, operations, and analytics teams (B2B/Enterprise)
- Mission or purpose: To build autonomous coworkers for financial analysis that empower teams to make correct decisions, faster — reducing weeks-long processes to minutes.

## Products & Services
- **[Sapien AI Platform]**: An AI-native analytics platform that connects directly to live ERP, warehouse, and spreadsheet data (SAP, NetSuite, Snowflake, BigQuery, Excel, on-prem ERPs). It provides 24/7 autonomous analysis, anomaly detection, driver-based forecasts, variance analysis, and root-cause explanations. Every answer is traceable to source transactions and logic, enabling finance teams to verify and intervene. (Type: AI SaaS Platform)

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding of **$8.7M** (Seed round, October 2024)
- **Notable Investors/Partners**: Lead investors General Catalyst and Neo, with participation from K5. Angel investors include executives and founders from Ramp, Cognition, Google, OpenAI, Stripe, Notion, Adobe, Pilot, and more (e.g., Russell Kaplen, Claire Hughes Johnson, Sabrina Hahn, Scott Belsky).
- **Growth Signals**: Headcount grew **266.7% YoY** (to 16 employees as of mid-2025). LinkedIn followers grew **113.8% YoY** (to 3,122). The company has **20 active job postings** (monthly job postings up 81.8%). They are shipping rapid product iterations and expanding into enterprise-grade features.

## Competitive Advantages
- **Persistent Business Context**: Sapien maps a company’s org structure, business rules, and definitions (e.g., "contribution margin") to its data, so context is not lost between queries.
- **Live Data Connectivity & Traceability**: Unlike general-purpose LLMs (ChatGPT, Claude, Gemini), Sapien stays connected to live ERP/warehouse data and provides fully traceable answers down to source transactions, significantly reducing hallucination risk.
- **SOC 2 Type II & SOC 3 Certified**: Built with enterprise-grade security and trust, with role-based access controls and a policy of never training on customer data.
- **Deep ERP Expertise**: Works across complex, legacy systems (e.g., SAP, 20-year-old on-prem ERPs) that most AI tools cannot handle.

## Strategic Focus
- **Product Expansion**: Shipping more powerful product iterations for customers, particularly for enterprise use cases (10-Q reporting, global pricing scenarios, margin variance analysis).
- **Team Building**: Aggressively hiring across engineering, operations, and GTM to build a "talent-dense, high-velocity team" tackling hard AI research and product problems.
- **Enterprise Go-to-Market**: Scaling from mid-market to Fortune 500, with a focus on automating recurring finance workflows and delivering 8-figure bottom-line impacts for customers.

## Why Work Here
- **Culture**: Values ownership (end-to-end ownership of research, product, and customer work), inquisitiveness (always pushing for the "why" and "so what"), and adaptability (solving different, harder problems). The team is described as "talent-dense" and sits at the intersection of complex AI research, beautifully simple product, and high-impact use cases.
- **Work Policy**: On-site in New York City (NYC). All open roles are listed as on-site/full-time.
- **Notable Perks/Engineering Culture**: Engineers own key aspects of research, product, and customer work end-to-end. The company builds systems that understand context, adapt in real time, and help teams make sharper decisions. Open-ended problem scopes are a core part of the day-to-day.

## Sources
1. [sapien.ai](https://sapien.ai/)
2. [sapien.ai/careers](https://sapien.ai/careers)
3. [linkedin.com](https://www.linkedin.com/company/getsapien)
4. [sapien.ai/blog](https://sapien.ai/blog/sapien-seed-round-general-catalyst)
5. [sapien.ai/solutions](https://sapien.ai/solutions/ai-analytics-for-enterprise)

## Other roles at Sapien

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