Senior AI Scientist - Mid-Market Intelligence

Company Overview Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide using products such as Turbo Tax, Credit Karma, Quick Books, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview Company Overview Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview Intuit is looking for an innovative and hands-on Senior AI Scientist to join the Mid-Market Intelligence team.

Mid-Market is one of the fastest growing segments of the business, and we are on a mission to build the industry's first truly AI-native ERP. The Intelligence team builds the AI at the heart of that product — leveraging the state of the art in AI and agentic technology to enable AI-native experiences where intelligent automation and seamless AI-to-human collaboration are designed in from the ground up, not bolted on.

Come join our collaborative and creative group of AI scientists and machine learning engineers and build models and agentic systems that directly change how mid-market businesses run their operations. In this role you will be building, evaluating, and deploying AI systems spanning large language models, agentic architectures, and classical machine learning.

Responsibilities Responsibilities
- Apply the state of the art in AI and agentic technology — LLMs, multi-agent architectures, tool use, retrieval (RAG), prompt and context engineering, and fine-tuning — to enable AI-native product experiences for mid-market ERP customers
- Perform hands-on data analysis and modeling with huge, real-world business datasets (financials, operations, transactions)- Build intelligent systems that proactively capture data signals, prevent issues before they occur, automate processes, and improve customer decision making — combining generative AI with classical machine learning (supervised and unsupervised) where each is strongest
- Design and build rigorous evaluation frameworks for LLM and agentic systems — offline evals, golden datasets, LLM-as-judge approaches, and quality/safety guardrails — and treat evaluation as a first-class deliverable
- Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products for AI-native workflows, including human-in-the-loop and explainability patterns
- Discover data sources, get access to them, import them, clean them up, and make them "model-ready." You need to be willing and able to do your own ETL
- Create and refine features, context, and retrieval strategies from the underlying data. You'll enjoy developing just enough ERP subject matter expertise to have an intuition about what signals might make your models and agents perform better, and then you'll lather, rinse and repeat
- Run regular A/B tests and online experiments, gather data, perform statistical analysis, draw conclusions on the impact of your optimizations, and communicate results to peers and leaders
- Explore new AI research, design, and technology shifts in order to determine how they might connect with the customer benefits we wish to deliver, in a landscape that evolves month to month

Qualifications- BS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.)- 3+ years of industry experience with AI science, spanning both classical…