Time since we first saw it
Day 164
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From 51 similar postings that came down. Coming down is not always a hire.
San Francisco · New York City · San Francisco, California, United States
Open 5 months, first seen by us 164 days agoLocation type: On-siteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: EngineeringFrom the employer’s posting
Build tool-using LLM agents that surface insights and execute approved tasks
Refine invoice matching, payment reconciliation, and financial document processing
Apply and optimize LLMs and RAG systems for financial use cases
Build reliable, cost-efficient AI pipelines from ingestion to inference
Set up golden datasets, agent tracing, and A/B testing to ship with confidence
Build tool-using LLM agents that surface insights, recommend next steps, and execute approved tasks
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
Stuut is the AI coworker that runs order-to-cash for the world’s leading enterprises.
In the employer’s words · Read in context · Company website ↗
Open 5 monthsWe first saw this posting 164 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 164
Up longer than most. Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
2 open jobs
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- 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
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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
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We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
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
Benefits (for U.S.-based full-time employees)
Medical, dental & vision insurance coverage for you
401(k) & Match
Equity
Flexible PTO
Parental Leave
Stuut is an equal opportunity employer committed to building a team with diverse backgrounds, perspectives, and experiences. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law.
We are also committed to providing reasonable accommodations throughout the application and interview process. If you need any accommodations, please do not hesitate to reach out.
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San Francisco, California, United States
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