Sr Staff AI Scientist, Agentic AI
Intuit
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San Diego, CA
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Mid-Senior level
Posted March 5, 2026
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Responsibilities
Responsibilities
- Drive the initiation and design of complex agent model solutions.
- Lead the end-to-end architecture and implementation of the team’s work, ensuring accountability for high-quality code, robust design, cost efficiency, and implementation standards.
- Apply cutting-edge techniques, including Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning, to design and train robust, self-improving AI agents on large, real-world datasets.
- Practice strong leadership and communication skills to influence teams and evangelize the impact of Agentic AI across the broader organization.
- Partner closely with Product Managers, Software Engineers, and Designers to define problem statements, success criteria, align model metrics with core business goals, and ensure successful delivery and integration of complex AI solutions.
- Work independently and proactively in a fast-paced environment.
- Quickly research, explore, and enable new ML and Agentic technologies, staying current with developments in academia and industry to solve Intuit customer problems.
- Develop efficient techniques for designing and evaluating agentic systems
Not Met Priorities
What still needs stronger evidence
Requirements
- Have 8+ years of industry experience with data science.
- Have 5+ years of hands-on expertise in advanced ML paradigms essential for agent development, such as Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning.
- Have extensive prior experience building end-to-end, reusable data and model pipelines from data acquisition through to complex model/agent output delivery in a production environment.
- Have experience developing and evaluating complex agentic AI systems
- Have experience orchestrating multi agent systems
- Have authored papers in top conferences and journals on Reinforcement learning or Deep Learning systems
Preferred Skills
- Have experience developing and evaluating complex agentic AI systems
- Have experience orchestrating multi agent systems
- Have authored papers in top conferences and journals on Reinforcement learning or Deep Learning systems
Education
- (Not required) – Have a BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
Overview
CG AI is in the business of creating impactful agent powered experiences that save time and money for our customers. We have a team striving to make agents more effective, focusing on complex planning, flawless long-term operation, extensibility through tools and APIs, multi-agent coordination, and persistent memory.
If you like designing and deploying effective agent systems that can successfully reason, plan, and take action to solve complex, high-value user challenges - come, join us.
In this high-impact role, you will be a key technical leader in architecting and delivering next-generation Agentic AI solutions that ensure our customers experience more money, less work, and complete confidence.
Responsibilities
Drive the initiation and design of complex agent model solutions. Lead the end-to-end architecture and implementation of the team’s work, ensuring accountability for high-quality code, robust design, cost efficiency, and implementation standards.
Apply cutting-edge techniques, including Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning, to design and train robust, self-improving AI agents on large, real-world datasets.
Practice strong leadership and communication skills to influence teams and evangelize the impact of Agentic AI across the broader organization.
Partner closely with Product Managers, Software Engineers, and Designers to define problem statements, success criteria, align model metrics with core business goals, and ensure successful delivery and integration of complex AI solutions.
Work independently and proactively in a fast-paced environment. Quickly research, explore, and enable new ML and Agentic technologies, staying current with developments in academia and industry to solve Intuit customer problems.
Develop efficient techniques for designing and evaluating agentic systems
Qualifications
Have 8+ years of industry experience with data science.
Have a BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
Have 5+ years of hands-on expertise in advanced ML paradigms essential for agent development, such as Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning.
Have extensive prior experience building end-to-end, reusable data and model pipelines from data acquisition through to complex model/agent output delivery in a production environment.
Strong Candidates May Also
Have experience developing and evaluating complex agentic AI systems
Have experience orchestrating multi agent systems
Have authored papers in top conferences and journals on Reinforcement learning or Deep Learning systems
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
Bay Area California $ 222,000- 300,000
Southern California $ 204,000- 276,500
CG AI is in the business of creating impactful agent powered experiences that save time and money for our customers. We have a team striving to make agents more effective, focusing on complex planning, flawless long-term operation, extensibility through tools and APIs, multi-agent coordination, and persistent memory.
If you like designing and deploying effective agent systems that can successfully reason, plan, and take action to solve complex, high-value user challenges - come, join us.
In this high-impact role, you will be a key technical leader in architecting and delivering next-generation Agentic AI solutions that ensure our customers experience more money, less work, and complete confidence.
Responsibilities
Drive the initiation and design of complex agent model solutions. Lead the end-to-end architecture and implementation of the team’s work, ensuring accountability for high-quality code, robust design, cost efficiency, and implementation standards.
Apply cutting-edge techniques, including Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning, to design and train robust, self-improving AI agents on large, real-world datasets.
Practice strong leadership and communication skills to influence teams and evangelize the impact of Agentic AI across the broader organization.
Partner closely with Product Managers, Software Engineers, and Designers to define problem statements, success criteria, align model metrics with core business goals, and ensure successful delivery and integration of complex AI solutions.
Work independently and proactively in a fast-paced environment. Quickly research, explore, and enable new ML and Agentic technologies, staying current with developments in academia and industry to solve Intuit customer problems.
Develop efficient techniques for designing and evaluating agentic systems
Qualifications
Have 8+ years of industry experience with data science.
Have a BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
Have 5+ years of hands-on expertise in advanced ML paradigms essential for agent development, such as Causal-ML, Reinforcement Learning, Online Learning, and Deep Learning.
Have extensive prior experience building end-to-end, reusable data and model pipelines from data acquisition through to complex model/agent output delivery in a production environment.
Strong Candidates May Also
Have experience developing and evaluating complex agentic AI systems
Have experience orchestrating multi agent systems
Have authored papers in top conferences and journals on Reinforcement learning or Deep Learning systems
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
Bay Area California $ 222,000- 300,000
Southern California $ 204,000- 276,500