Member of the Technical Staff — AI/ML

About Stuut

Stuut is the AI coworker that runs order-to-cash for the world’s leading enterprises. Across order management, credit, collections, payments, cash application, disputes and deductions, Stuut does the work end to end and keeps going until the cash hits the bank.

Over 150 companies, spanning the mid-market to the Fortune 50, including Honeywell, ZoomInfo and PerkinElmer, use Stuut to unlock up to 40% more cash flow and cut DSO by 47%. More than $3 billion has moved through the platform to date.

Founded in New York by Tarek Alaruri and Ben Winter, Stuut has raised $93 million from Insight Partners, Andreessen Horowitz, M12, Microsoft’s Venture Fund, and others. Learn more at stuut.ai.

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
• US Compensation
• Top-of-market salary and equity package