Base Salary
$180k - $244k/yr
Responsibilities
- Design, build, and improve Python-based agentic AI systems with multi-step planning, tool use, and structured output generation.
- Produce deterministic, reviewable artifacts that human experts can inspect, correct, and approve before runtime execution.
- Design human-in-the-loop review experiences that provide domain experts visibility and control.
- Own evaluation methodology, including production-derived ground-truth datasets, output-correctness metrics, trajectory-quality metrics, and evaluation-driven improvements.
- Reason across structured and semi-structured data from multiple systems, trace entities to systems of record, and partner with owning teams to establish access.
- Move capabilities from experimentation into production through responsible AI review, service deployment, tracing, observability, and operational readiness.
- Evaluate and migrate between emerging agentic frameworks, protocols, and tooling.
- Prototype with generative AI and independently resolve cross-team dependencies.
- Partner with product managers, domain experts, and engineering teams to align capabilities with business outcomes.
Requirements
- A master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
- At least 4 years of experience in the offered role or in an AI Scientist, Machine Learning, or Data Science-related occupation.
- Experience building agentic AI applications in Python using orchestration frameworks such as LangGraph, LangChain, Agent SDKs, or equivalent.
- Experience adopting and migrating between agentic frameworks, protocols, and tooling, including Model Context Protocol.
- Experience designing evaluation frameworks for large language model and agentic systems, including ground-truth datasets, output-level metrics, trajectory-level metrics, and evaluation-driven improvement.
- Experience applying large language models to production problems, including prompt design, retrieval-augmented generation, context management, and containment of non-determinism.
- Ability to reason over structured and semi-structured data across systems using schema interpretation, entity relationship modeling, SQL, and related data retrieval tools.
- Foundational machine learning knowledge sufficient to evaluate model behavior, failure modes, and evaluation validity.
- Experience deploying and operating services in cloud environments such as AWS, including containerized deployment, tracing, and observability tooling.
- Ability to use generative AI tools to rapidly prototype and deliver production-ready solutions.
Benefits
- Competitive compensation package with pay-for-performance rewards.
- Potential eligibility for a cash bonus, equity rewards, and benefits under applicable plans and programs.
- Expected base pay range of $180,000–$243,500 for the Mountain View location.
- Mountain View work location; the posting does not specify a remote or hybrid arrangement.
Categories
About Intuit
Intuit is a global technology platform that helps our customers and communities overcome their most important financial challenges. Serving millions of customers worldwide with TurboTax, QuickBooks, Credit Karma and Mailchimp, we believe that everyone should have the opportunity to prosper and we work tirelessly to find new, innovative ways to deliver on this belief. We encourage conversations on this page and will not delete comments that follow our terms of use. In order to keep this a safe community, the below posts may be removed: Repeated posts of the same content, spam or posts from fake accounts or profiles, offensive language or material, threats to others in the community, posts deliberately aimed to have a negative effect on the community or conversations.