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About This Role
Overview
At Intuit we’re investing in a culture of builders, fostering an environment where innovation, creativity, and bold thinking are encouraged. This builder mindset is critical as we accelerate toward AI-native experiences that solve our customers’ most important problems.
We are looking for a Group (M3) Engineering Manager to provide engineering leadership across our Vertical Capability Platform and a portfolio of select emerging industry solutions within Intuit Enterprise Suite (IES). You will help evolve and drive IES from a horizontal ERP into an AI-native, industry-differentiated platform, delivering the financial and operational depth Mid-Market customers need to run their businesses end to end.
You will drive the vision that enables deep industry capabilities without creating one-off vertical stacks—turning common industry patterns into durable platform capabilities while delivering differentiated industry experiences on IES. You will help make each new vertical faster to build, easier to scale, and AI-native by default.
Responsibilities
- Technology leaders at Intuit think strategically and drive for results - build high-performing teams, foster innovation, and create an environment where teams embrace new ideas that produce outstanding outcomes for our customers.
- Lead teams in creating and bringing customer-driven software products to market that solve current customer needs while building durable capabilities for the future.
- Drive technology strategy and guide key technical designs and decisions for the Vertical Platform and industry solutions, balancing customer needs, engineering velocity, scalability, and long-term maintainability.
- Guide teams in building scalable, reliable, and AI-native platform capabilities that can be leveraged across multiple industry solutions.
- Bring out the best ideas from engineers by empowering them, providing technical context and direction, and leading by example.
- Create a shared vision and build strong cross-functional relationships and alignment with partners across Product Management, Design, Architecture, Program Management, and other engineering teams.
- Foster a culture of technical excellence, innovation, operational excellence, and continuous improvement across your teams.
- Mentor and develop engineering leaders and engineers, helping them strengthen their technical and leadership skills and advance their careers.
- Stay abreast of advancements in AI, automation, and emerging technologies, and help teams identify opportunities to apply them to meaningful customer problems.
Qualifications
- 8+ years of experience as an established technical leader of software engineering teams that have successfully delivered large-scale business applications and customer-driven software products.
- Demonstrated experience leading positive change, empowering people, cultivating product and technology visions and innovative solutions, and fostering effective engineering teams.
- Adept at articulating product vision and driving future roadmaps with strong business acumen.
- Ability to think and act strategically across stakeholders.
- Passion for being at the leading edge of technology, with 12–14+ years of hands-on software development experience across backend and frontend technologies.
- Experience with large-scale distributed systems and cloud technologies such as AWS and GCP
- Experience leading AI-native applications using LLMs, agents, knowledge systems, and evaluation frameworks.
- Experience with ERP, financial systems, industry SaaS, or complex B2B workflows is highly desirable.
- Proven track record of execution, engineering excellence, and customer obsession.
- Proven track record of working effectively across organizational boundaries.
- Strong verbal and written communication skills.
- BS or MS in Computer Science or a related field, or equivalent work experience.
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:
Mountain View $244,000 - $330,000
Salary Context
This $244K-$330K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Intuit, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($287K) sits 30% above the category median. Disclosed range: $244K to $330K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Intuit AI Hiring
Intuit has 32 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, AI Software Engineer, MLOps Engineer. Positions span Mountain View, CA, US, San Diego, CA, US, New York, NY. Compensation range: $116K - $369K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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