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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 and Page One.
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 midmarket 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
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