Distinguished Engineer, Intuit Intelligence, ML & AI

What you'll do

• Define the long-term AI and ML strategy by connecting scientific advances to customer needs and production constraints.
• Architect and build agents that reason over context, retrieve information, use tools, and coordinate workflows.
• Establish reusable approaches for agent orchestration, context management, and failure recovery.
• Guide model selection, adaptation, training, and inference decisions based on quality, latency, and cost tradeoffs.
• Build evaluation systems to measure model quality, task completion, robustness, safety, and customer value.
• Establish production practices for monitoring, experimentation, and model and agent lifecycle management.
• Address technical challenges in grounding, uncertainty, generalization, permissions, privacy, and reliable execution.
• Develop firsthand judgment by advancing promising ideas from experiments into validated product capabilities.

What we're looking for

• Deep expertise in AI science and ML, including statistical learning, deep learning, experimental design, and rigorous evaluation.
• Demonstrated experience building and operating production AI systems and agents that perform consequential workflows.
• Strong understanding of foundation models, retrieval, tool use, agent orchestration, and techniques for adapting models to domain needs.
• A record of translating research into scalable products and reusable technical capabilities.
• Strong software and systems engineering judgment with the ability to influence technical direction across organizations.
• Ability to explain scientific uncertainty and technical tradeoffs clearly to executive and technical audiences.
• Ability to distinguish improvements in model behavior from improvements in system reliability and customer outcomes.