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Need H1B candidate

Job Description:

We are seeking a self-motivated, hands-on Principal AI Engineer who operates with a high degree of autonomy and builds impactful products with high velocity to join Intuit’s Foresight organization.

You will be responsible for leveraging the latest advances in AI to solve complex, high-impact technical problems that unlock entirely new AI-driven experiences through the new 0 ? 1 AI native products that you will build. You will also help transform the end-to-end Product Development Lifecycle (PDLC) by applying AI to improve engineering productivity, software quality, reliability, security, and operational excellence across the software development lifecycle.

Your work will directly shape how millions of Intuit’s customers, both small businesses and individuals, prosper through the effective use of AI within our platforms and products.

If you are a builder who loves to ship fast, learn continuously, and independently drive impact, then this is the right role for you.

Responsibilities

Shape and execute on a multi-year technical roadmap in partnership with Intuit’s AI leadership, ensuring that Intuit stays on the leading edge of AI innovation through incubation and development of emerging technologies and AI-enabled Product Development Lifecycle (PDLC) capabilities.

Build end-to-end solutions that demonstrate how the latest advances in AI can drive transformative new experiences for our customers.

Build AI-powered capabilities that accelerate and improve the software engineering lifecycle, enabling measurable gains in developer productivity, software quality, reliability, security, and operational excellence through AI-assisted development workflows.

Collaborate closely with business units and platform teams to accelerate testing and deployment of new technologies and capabilities into Intuit’s products and platforms.

Ensure excellence in data quality, model evaluation, and lifecycle management through rigorous monitoring, testing, and retraining practices.

Champion responsible AI practices, ensuring models are fair, transparent, and trustworthy.

Mentor and grow AI talent, championing a culture of innovation, ethics, and rigor.

Contribute through publications, patents, talks, or open source contributions to maintain Intuit’s position on the forefront of AI.

Qualifications

BS / MS / Ph.D. in Computer Science, Statistics, Applied Mathematics, Physics, Operations Research or related discipline.

Deep technical AI expertise especially in areas like training LLMs, reasoning models, multi-modal models and their application to Forecasting and Planning, Decision Making Under Uncertainty, Multi-objective Optimization, Learning from Human Feedback, Data Cognition, and Deep Personalization to build production-grade scalable AI agents and systems.

8+ years of experience or significant demonstrated impact developing and deploying AI solutions at scale that successfully solve challenging customer problems.

AI Tools Fluency: Hands-on experience using AI coding tools (e.g., Claude Code, Cursor, Codex) to augment and accelerate your daily development workflows.

Experience applying AI across the Product Development Lifecycle (PDLC), including AI-assisted software design, development, testing, deployment, observability, and engineering operations, with demonstrated impact on engineering productivity, software quality, reliability, or security.

Experience building large-scale Machine Learning applications on cloud platforms like AWS, GCP, or Azure is a strong plus.

Velocity and Adaptability: An aggressively entrepreneurial spirit with a track record of moving fast, delivering results quickly, and rapidly adopting AI technologies and AI-enabled engineering practices to improve software delivery and customer outcomes.

Customer Obsession: A strong desire to be close to the customer, with demonstrated experience running A/B tests, prototypes, or rapid user experiments.

Strong Computer Science / Data Science fundamentals including data structures, algorithms, performance complexity, data analysis, model training, A/B testing, and MLOps practices.