Intuit is looking to solve the problem of empowering experts and customers across its ecosystem by building an Agentic AI Framework to make data analytics AI-native, embedding agents into dashboards, reports, and workflows to augment decision-making, democratize knowledge, and accelerate speed-to-insight across the Customer Success ecosystem.
Requirements
- Strong Hands-on experience developing agentic AI workflows using modern Python-based frameworks (e.g., LangGraph, LlamaIndex, or similar) to build systems that integrate large language models, RAG, contextual reasoning, and dynamic tool or data integration for real-world applications.
- Deep understanding of agentic AI concepts, such as orchestration, memory management, context engineering, vector embeddings and semantic search, and evaluation/observability frameworks that enable autonomous reasoning and workflow automation.
- Experience developing and deploying services and APIs in cloud-native environments (e.g., AWS or GCP)
- Familiarity with the Model Context Protocol (MCP) and its use in connecting AI systems with external tools, data sources, and contexts to enable richer, more adaptive agentic workflows.
- 10+ years of experience in data science and machine learning with a proven ability to deliver production-grade ML/AI solutions.
- BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
- Demonstrated success in cross-functional collaboration partnering with data scientists, engineers, and product teams to translate complex AI capabilities into impactful solutions.
Responsibilities
- Drive the design, development, and scaling of agentic AI capabilities that embed autonomous reasoning and decision support into dashboards, reports, and workflows—powering intelligent, data-driven analytics across the Customer Success ecosystem.
- Develop and deploy AI software components, including large language model inference, context engineering, vector embeddings & semantic search, evaluation, governance, and observability.
- Define and refine technical requirements for AI models, agent orchestration logic, and human-in-the-loop processes—balancing user experience with the precision required in high-stakes decision environments.
- Drive the application of AI in BI, embedding AI agents into analytics tools and workflows to automate insight generation and enable natural language interaction with business data.
- Collaborate with cross-functional partners—including data scientists, engineers, product managers, and senior leaders—to translate strategic goals into scalable, high-impact AI solutions.
- Champion best practices in applied ML/AI through robust evaluation, monitoring, and experimentation frameworks that ensure reliability, transparency, and ethical integrity of deployed systems.
- Build strong partnerships and influence roadmaps across teams to ensure cohesive strategy and execution for agentic AI initiatives.
Other
- BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
- Excellent communication, collaboration, and problem-solving skills, with the ability to work effectively across technical and non-technical teams.
- Ability to present complex technical concepts clearly, conducting meetings and presentations that make AI and data science topics accessible to diverse audiences.
- Mentor and elevate peers across the data science and engineering community, fostering a culture of innovation, technical excellence, and continuous learning.
- Ability to work effectively across technical and non-technical teams.
