---
title: 'Member of the Technical Staff — AI/ML at Stuut'
canonical: 'https://feeny.ai/job/member-of-the-technical-staff-ai-ml-stuut-san-francisco-ze39zj5kj9mn'
type: 'job'
last_seen: '2026-09-14'
---

# Member of the Technical Staff — AI/ML at Stuut

- **Company:** Stuut
- **Location:** San Francisco, CA
- **Compensation:** $220k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-08-10
- **Last confirmed live:** 2026-09-14
- **Apply:** https://jobs.ashbyhq.com/stuut-ai/37cc28af-0ce7-4ddb-a099-6fb88b0b593f

## Job description

Stuut is transforming accounts receivable for B2B companies—making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We're backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures, Page One and Microsoft.

## The Role

We’re hiring a Member of Technical Staff – AI/ML to design, build, and deploy AI-powered systems that solve real-world financial operations challenges. You’ll take state-of-the-art AI research and translate it into production-grade features that deliver measurable customer impact. From intelligent invoice matching to automated payment reconciliation, you’ll create scalable, reliable AI applications that integrate seamlessly into our platform.

This is a hands-on role for an engineer who thrives at the intersection of AI innovation and practical business application — turning cutting-edge models into real-world value for mid-market CFOs

## What You’ll Do

- Create production-ready AI applications and agentic systems that address customer financial workflow challenges
- Build tool-using LLM agents that surface insights, recommend next steps, and execute approved tasks — not just chatbots
- Refine capabilities like invoice matching, payment reconciliation, and financial document processing
- Apply and optimize LLMs and RAG systems for financial use cases, including fine-tuning on proprietary data where it moves the needle
- Build robust AI pipelines from ingestion to inference — reliable, maintainable, and cost-efficient through smart model routing
- Stand up golden datasets, agent tracing, regression-on-PR, and A/B testing so we ship confidently and catch silent regressions
- Partner with Product, Engineering, Data, and customers to translate business needs into AI solutions
- Treat every AI feature as a continuously-improving system — instrument everything, iterate

You Might Be a Fit If You…

- Have 5+ years of AI/ML experience
- Have shipped agentic products in production and understand the failure modes (tool use, planning, state, recovery, human-in-the-loop)
- Have integrated and fine-tuned LLMs, and built RAG systems for document- or data-intensive workflows
- Have trained and deployed classical ML models (risk scoring, forecasting, ranking, or similar) — feature engineering, model selection, evaluation, calibration
- Have strong opinions on AI/ML evals — golden datasets, offline + online evaluation, statistical significance, evals in CI
- Are familiar with LLM observability tooling (LangSmith, Braintrust, Arize, or similar) and treat tracing as table stakes
- Understand MLOps fundamentals: deployment, monitoring, A/B testing, model and prompt versioning, feature stores
- Are fluent in Python and modern AI/ML tooling (PyTorch, Transformers, scikit-learn, XGBoost, vLLM, LangChain/LlamaIndex, or equivalent)
- Have shipped AI/ML products that solved real business problems, not just prototypes
- Can translate business requirements into clear technical solutions
- Bonus: experience with model routing across providers
- Bonus: fintech, B2B SaaS, or AR/AP domain experience
- Are plugged into the AI/ML community and energized by bringing AI to real-world use cases

## Compensation

- Top-of-market salary and equity package
- Benefits (for U.S.-based full-time employees)
- Medical, dental & vision insurance coverage for you
- 401(k) & Match
- Equity
- Flexible PTO
- Parental Leave

## About Stuut

## Company Overview
- **One-liner**: Stuut provides an AI-powered platform that autonomously handles the entire accounts receivable (AR) process, from customer outreach to payment collection, to increase cash flow.
- **Entity Type**: Private (Series A)
- **Headquarters**: New York, New York, United States
- **Founded**: 2024
- **Founders**: Tarek Alaruri (CEO), Ben Winter (COO), Adam Chaarawi (Co-founder, Engineering)

## Core Business
- **Primary industries**: Accounts receivable automation, financial operations, order-to-cash software.
- **Target customers**: B2B – finance and accounting teams at companies using ERPs such as SAP, Oracle, NetSuite, and Dynamics (mid-market to enterprise).
- **Mission**: Transform accounts receivable from manual work into automated cash collection.

*Source: [stuut.ai](https://www.stuut.ai/), [stuut.ai/about](https://www.stuut.ai/about)*

## Products & Services
Stuut’s AI agent covers the full order-to-cash cycle with these modules:

- **Collections**: Proactively reaches out before invoices are overdue, finds billing contacts, and engages via email, SMS, and voice.
- **Cash Application**: Automatically matches incoming payments to invoices and provides click-to-pay functionality.
- **Deductions**: Autonomously identifies, investigates, and resolves deductions, recovering revenue that would otherwise be lost.
- **Disputes**: Handles disputes end-to-end – gathering documentation, communicating with customers, and maintaining detailed audit trails.
- **Payments**: Processes incoming payments and matches them to invoices.
- **Credit**: Evaluates customer creditworthiness and recommends optimal credit terms.

All modules operate on a unified AI that learns each customer’s payment patterns and preferences, personalizing every interaction. The platform integrates with major ERPs in 3–4 days.

*Source: [stuut.ai](https://www.stuut.ai/)*

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metrics**:
  - **Total Funding**: $29.5M (Series A led by Andreessen Horowitz, closed ~late 2025) – also $35.41M reported by CB Insights (possibly including prior rounds).
  - **Revenue**: Not publicly available.
  - **Employees**: 63 (as of mid-2026); monthly headcount growth of +11.1%, yearly growth of +212.5%.
  - **Active job postings**: 36 (monthly posting growth +56.5%, yearly +800%).
- **Notable Investors**: Andreessen Horowitz (lead, Series A), Khosla Ventures, Activant Capital (lead, Seed), 1984 Ventures, Carya Venture Partners, Page One Ventures.
- **Growth Signals**: 
  - Doubled headcount year-over-year.
  - Claims 40% average cash flow increase and 70% reduction in manual tasks for customers.
  - Linkedin followers grew 57.8% year-over-year to ~25,000.
  - Expanded from pilot to full product suite (6 modules) within 18 months of founding.

*Sources: [linkedin.com](https://www.linkedin.com/company/stuut), [cbinsights.com](https://www.cbinsights.com/company/stuut), [stuut.ai](https://www.stuut.ai/)*

## Competitive Advantages
- **True autonomy**: Unlike traditional AR software that provides better tools, Stuut’s AI agents execute complete workflows independently (end-to-end) without human oversight.
- **Rapid deployment**: 3–4 days vs. 6–18 months for legacy solutions.
- **Contextual intelligence**: Tracks every customer interaction across email, SMS, and voice, getting smarter over time.
- **Unified platform**: Collections, cash application, deductions, disputes, payments, and credit in one system – not a patchwork of point solutions.
- **ERP-native integration**: Works out-of-the-box with SAP, Oracle, NetSuite, Dynamics.

*Source: [stuut.ai](https://www.stuut.ai/)*

## Strategic Focus
- Continue building out the AI agent’s capabilities (e.g., adding more dispute and credit features).
- Scale the go-to-market team (open roles include Director of Revenue Operations, Product Marketing Manager) to capture the large AR automation market.
- Maintain rapid deployment and customer success to drive word-of-mouth growth.
- Deepen integrations with additional ERP systems and expand into adjacent financial workflows.

*Source: [linkedin.com](https://www.linkedin.com/company/stuut)*

## Why Work Here
- **Culture & values**: “Think independently,” intellectual curiosity, ownership, and proactive initiative. The team is described as operations and product nerds who hate bureaucracy.
- **Work model**: In-office in New York City (NYC headquarters). Built In lists “OnSite Workspace” with typical time on-site: None? (conflicting; but job postings mention hybrid). Likely a hybrid policy with strong in-office expectation.
- **Perks & benefits** (from Built In):
  - Healthcare benefits, childcare benefits, generous parental leave.
  - Company equity and performance bonuses.
  - Continuing education stipend, mentorship program, online course subscriptions.
  - Quarterly engagement surveys, diversity-focused ERGs, diversity recruitment program.
- **Growth opportunity**: High-growth startup (headcount up 212% YoY) with backing from top-tier VCs (a16z, Khosla). Employees get to shape the product and culture early.
- **Open roles**: 36 active positions across engineering (AI/ML, fullstack, data), product design, marketing, and revenue operations – sign of scaling.

*Sources: [builtin.com](https://builtin.com/company/stuut), [linkedin.com](https://www.linkedin.com/company/stuut)*

## Sources
1. [stuut.ai – Homepage](https://www.stuut.ai/)
2. [stuut.ai – About page](https://www.stuut.ai/about)
3. [linkedin.com – Stuut company page](https://www.linkedin.com/company/stuut)
4. [builtin.com – Stuut careers and perks](https://builtin.com/company/stuut)
5. [cbinsights.com – Stuut profile](https://www.cbinsights.com/company/stuut)

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