Prototype and build agent builder frameworks and embedded AI experiences, taking cutting-edge agentic AI concepts from early exploration to product-ready implementations
Drive rapid prototyping and experimentation to move from proof-of-concept to high-accuracy, performant systems
Set best practices for ML tooling and developer workflows; mentor other engineers on AI craft
Stay ahead of emerging GenAI and ML developments and identify where they improve existing products
Collaborate closely with AI scientists, product, and design to navigate ambiguity and ship next-generation AI-driven experiences
Architect and build full-stack, AI-native applications end-to-end, from backend services to production LLM integrations
Set best practices for application architecture; mentor other engineers on software engineering craft
Qualifications
BS, MS, or PhD in Computer Science or equivalent practical experience
8+ years building production AI/ML systems; prior experience leading an engineering effort a plus
Strong CS fundamentals - data structures, algorithms, system design - plus solid ML fundamentals (classification, regression, clustering, neural networks)
Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, Pandas/NumPy)
Practical experience with LLMs: prompt engineering, fine-tuning, and frameworks like LangChain
Experience building or operating agentic systems, agent frameworks, or long-term memory/context architectures for AI applications
Familiarity designing evaluation frameworks or offline/online eval pipelines for measuring model and agent quality
Cloud platform experience for ML workloads (AWS, including SageMaker)
Track record of launching AI integrations in production and evaluating their real-world impact
Strong cross-functional collaboration skills, partnering effectively with data scientists, product managers, and engineers across global teams
Proficiency in one or more full-stack languages (JavaScript, Java) and experience designing scalable services - microservices, relational/NoSQL data stores, Kubernetes
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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 $230,000- $250,000.
- The expected base pay range for this position is:
- Mountain View $202,500 - $274,000
