AI Engineer Jobs at Intuit with Visa Sponsorship
AI Engineer jobs at Intuit involve building machine learning infrastructure, intelligent financial products, and LLM-powered features across TurboTax, QuickBooks, and Credit Karma. The company has a consistent track record of sponsoring work visas for technical roles, making it a realistic target if you need sponsorship.
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Intuit is a global platform company that is on a mission to power prosperity around the world for consumers, small businesses and the self-employed. Across our leading brands - TurboTax, Credit Karma, QuickBooks, and Mailchimp - Intuit serves over 100M customers and is one of the few companies in the world to have both a thriving consumer and small business ecosystem. Intuit is known for its innovation track record, customer centricity, and its consistent recognition as a top place to work. This role leads the product strategy for Intuit’s internal AI developer platform — including GenAI developer tooling, agent frameworks, shared AI services, model access and routing, prompt and evaluation infrastructure, observability, cost visibility, and platform standards. You will not simply ship AI features; you will build the paved road that enables 1,000+ engineers to build production-ready AI capabilities with speed, trust, and consistency.
Responsibilities
- 10–15+ years of product leadership experience, with deep experience in platform, infrastructure, developer tooling, AI/ML, or enterprise SaaS products at scale.
- Demonstrated success building or scaling AI developer platforms, internal GenAI platforms, or shared AI services used by hundreds or thousands of engineers.
- Strong product judgment for platform adoption: you know how to make shared tooling the path of least resistance through strong developer experience, clear standards, and measurable adoption.
- Deep familiarity with modern GenAI platform capabilities, including agent orchestration, prompt management, evaluation frameworks, model routing, RAG/context services, model serving, observability, governance, and cost management.
- Proven ability to define what “production-ready AI” means across latency, reliability, safety, quality, cost, monitoring, explainability, and developer velocity.
- Track record translating complex technical platform investment into business outcomes, including adoption metrics, productivity gains, cost attribution, eval coverage, reliability, and risk reduction.
- Experience leading through influence across engineering, product, data science, security, legal, and business unit stakeholders with competing priorities.
- Strong people leadership experience, including developing senior IC PMs, setting clear product operating rhythms, and building a high-performing platform product organization.
- Customer-backed mindset with developers as the primary customer, balanced with a strong understanding of end-customer trust, safety, and business impact.
- AI fluency and curiosity, with a practical point of view on how GenAI platforms should evolve as models, tooling, governance expectations, and developer workflows change.
Qualifications
- Own the product vision, strategy, and roadmap for Intuit’s AI Foundations portfolio, including internal GenAI developer tooling, agent framework, shared AI services, model services, context and RAG capabilities, evaluation and monitoring, and AI infrastructure cost visibility.
- Build the internal equivalent of a purpose-built AI platform for Intuit’s engineering organization — enabling teams to create AI-powered experiences without rebuilding foundational capabilities in isolation.
- Drive developer adoption across business units by deeply understanding engineer workflows, reducing friction, and making standardized platform capabilities the fastest and safest way to ship AI.
- Establish clear platform success metrics, including active developer adoption, platform usage, time-to-production, review-cycle reduction, eval coverage, reliability, latency, cost efficiency, and production incident reduction.
- Scale production AI rigor by driving adoption of tracing, continuous evaluation, model and agent monitoring, guardrails, and quality measurement across Intuit’s AI experiences.
- Partner with engineering leaders to make high-quality platform tradeoffs across build vs. buy, standardization vs. flexibility, speed vs. reliability, and experimentation vs. enterprise readiness.
- Create visibility into AI platform ROI through cost attribution, usage insights, model performance monitoring, and executive-ready reporting that helps leaders fund what works.
- Define and operationalize AI platform standards that improve safety, consistency, governance, and developer velocity across Intuit.
- Lead cross-BU prioritization for shared AI platform capabilities, ensuring the roadmap reflects the highest-leverage needs of Intuit’s engineering teams and customers.
- Build, coach, and retain a world-class AI platform product management team with strong technical depth, customer empathy, and data-driven decision-making.
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:
Overview
Intuit is a global platform company that is on a mission to power prosperity around the world for consumers, small businesses and the self-employed. Across our leading brands - TurboTax, Credit Karma, QuickBooks, and Mailchimp - Intuit serves over 100M customers and is one of the few companies in the world to have both a thriving consumer and small business ecosystem. Intuit is known for its innovation track record, customer centricity, and its consistent recognition as a top place to work. This role leads the product strategy for Intuit’s internal AI developer platform — including GenAI developer tooling, agent frameworks, shared AI services, model access and routing, prompt and evaluation infrastructure, observability, cost visibility, and platform standards. You will not simply ship AI features; you will build the paved road that enables 1,000+ engineers to build production-ready AI capabilities with speed, trust, and consistency.
Responsibilities
- 10–15+ years of product leadership experience, with deep experience in platform, infrastructure, developer tooling, AI/ML, or enterprise SaaS products at scale.
- Demonstrated success building or scaling AI developer platforms, internal GenAI platforms, or shared AI services used by hundreds or thousands of engineers.
- Strong product judgment for platform adoption: you know how to make shared tooling the path of least resistance through strong developer experience, clear standards, and measurable adoption.
- Deep familiarity with modern GenAI platform capabilities, including agent orchestration, prompt management, evaluation frameworks, model routing, RAG/context services, model serving, observability, governance, and cost management.
- Proven ability to define what “production-ready AI” means across latency, reliability, safety, quality, cost, monitoring, explainability, and developer velocity.
- Track record translating complex technical platform investment into business outcomes, including adoption metrics, productivity gains, cost attribution, eval coverage, reliability, and risk reduction.
- Experience leading through influence across engineering, product, data science, security, legal, and business unit stakeholders with competing priorities.
- Strong people leadership experience, including developing senior IC PMs, setting clear product operating rhythms, and building a high-performing platform product organization.
- Customer-backed mindset with developers as the primary customer, balanced with a strong understanding of end-customer trust, safety, and business impact.
- AI fluency and curiosity, with a practical point of view on how GenAI platforms should evolve as models, tooling, governance expectations, and developer workflows change.
Qualifications
- Own the product vision, strategy, and roadmap for Intuit’s AI Foundations portfolio, including internal GenAI developer tooling, agent framework, shared AI services, model services, context and RAG capabilities, evaluation and monitoring, and AI infrastructure cost visibility.
- Build the internal equivalent of a purpose-built AI platform for Intuit’s engineering organization — enabling teams to create AI-powered experiences without rebuilding foundational capabilities in isolation.
- Drive developer adoption across business units by deeply understanding engineer workflows, reducing friction, and making standardized platform capabilities the fastest and safest way to ship AI.
- Establish clear platform success metrics, including active developer adoption, platform usage, time-to-production, review-cycle reduction, eval coverage, reliability, latency, cost efficiency, and production incident reduction.
- Scale production AI rigor by driving adoption of tracing, continuous evaluation, model and agent monitoring, guardrails, and quality measurement across Intuit’s AI experiences.
- Partner with engineering leaders to make high-quality platform tradeoffs across build vs. buy, standardization vs. flexibility, speed vs. reliability, and experimentation vs. enterprise readiness.
- Create visibility into AI platform ROI through cost attribution, usage insights, model performance monitoring, and executive-ready reporting that helps leaders fund what works.
- Define and operationalize AI platform standards that improve safety, consistency, governance, and developer velocity across Intuit.
- Lead cross-BU prioritization for shared AI platform capabilities, ensuring the roadmap reflects the highest-leverage needs of Intuit’s engineering teams and customers.
- Build, coach, and retain a world-class AI platform product management team with strong technical depth, customer empathy, and data-driven decision-making.
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:
See all 59+ AI Engineer Jobs at Intuit
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Get Access To All JobsTips for Finding AI Engineer Jobs at Intuit
Align your ML experience to Intuit's product stack
Intuit's AI teams work heavily on NLP, personalization, and document understanding within financial products. Frame your resume around those domains rather than generic deep learning experience. Reviewers are looking for signal that you understand production ML at scale.
Target roles that sit under established AI orgs
Intuit has dedicated AI and data platform organizations. Roles posted under those orgs are more likely to have defined sponsorship workflows than newer or experimental teams, which sometimes lack the HR infrastructure to move quickly on visa filings.
Get your credentials evaluated before applying
If your degree is from outside the United States, get a credential evaluation from a NACES-approved evaluator before your first interview. Intuit's immigration team will need this for the H-1B specialty occupation determination, and delays here can slow the entire petition timeline.
Understand how the H-1B cap affects your start date
If you're not already on a cap-exempt status like F-1 OPT or an existing H-1B, your petition enters the annual lottery. USCIS cap-subject petitions can only take effect October 1, so negotiate your offer timeline accordingly and ask HR which filing window applies to you.
Clarify LCA scope during the offer stage
The Labor Condition Application filed with DOL locks in your worksite and wage level. Before signing, confirm whether Intuit will list their Mountain View or New York offices, especially if your role is hybrid. A mismatched LCA worksite can require an amendment if your location changes.
Use Migrate Mate to find open AI Engineer roles at Intuit that explicitly support sponsorship
Not every Intuit job posting makes sponsorship eligibility obvious. Migrate Mate filters specifically for roles where sponsorship is confirmed, saving you from applying to positions where visa support was never on the table.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for AI Engineers?
Yes, Intuit sponsors H-1B visas for AI Engineer roles. The company works with immigration counsel to file cap-subject and cap-exempt petitions depending on your current status. If you're transitioning from F-1 OPT, Intuit can file during the regular cap season. If you hold an existing H-1B visa from another employer, a transfer is possible without waiting for the lottery.
How do I apply for AI Engineer jobs at Intuit?
Start by identifying open AI Engineer roles through Intuit's careers portal or Migrate Mate, which filters for positions with confirmed visa sponsorship. Tailor your application to reflect Intuit's specific AI focus areas: financial NLP, recommendation systems, and ML platform engineering. After applying, expect a recruiter screen followed by a multi-stage technical loop covering coding, ML system design, and product sense.
Which visa types does Intuit commonly use for AI Engineers?
Intuit sponsors H-1B, E-3 visa, TN visa, and F-1 OPT and CPT for AI Engineer roles, depending on your nationality and current status. Australian citizens are eligible for the E-3, which bypasses the H-1B lottery. Canadian and Mexican nationals in qualifying engineering roles may qualify for TN visa status. For permanent residency, Intuit also supports EB-2 and EB-3 Green Card sponsorship.
What qualifications does Intuit expect for AI Engineer roles?
Most AI Engineer roles at Intuit require a bachelor's or master's degree in computer science, machine learning, or a related technical field. Hands-on experience with large-scale ML systems, Python, and at least one major ML framework is expected. Roles closer to production engineering also weight distributed systems knowledge. Research-oriented positions often look for published work or experience with LLM fine-tuning and evaluation pipelines.
How do I time my application around the H-1B filing calendar?
USCIS opens H-1B registration in early March each year for the cap lottery. To be included, you need a signed offer by late February at the latest. If selected, your petition cannot take effect before October 1. F-1 OPT holders can bridge this gap using a timely filed extension. Coordinate your interview and offer timeline with Intuit's recruiters well in advance of the March window.