Member of the Technical Staff — AI/ML

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