Principal Software Engineer

Job Overview

We are looking for a Principal Software Engineer to lead the design and implementation of the next generation AI and machine learning systems that power our omnichannel marketing and CRM platform. This is a foundational role for a leader who will fuse scalable traditional AI/ML with cutting-edge generative and agentic systems. You will build the intelligent core of our recommendation and targeting systems, responsible for everything from attribution and conversion prediction to dynamic, LLM-powered creative generation. You won't just optimize an existing system; you will define and build the future of AI-driven marketing and CRM at Intuit.

Responsibilities

* AI Solution Architect: Design and deploy the sophisticated ML systems that power our marketing solutions. This includes both large-scale ranking and recommendation models and innovative generative AI solutions for dynamic marketing creative, personalized copy, and audience modeling.
* Pioneer Marketing Agents: Lead the application of LLMs for end-to-end marketing optimization. Develop and productionize systems for automated marketing generation, personalized content adaptation, and building conversational, agentic interfaces for campaign and customer relationship management.
* Own the End-to-End AI/ML Lifecycle: Take full ownership of the process from ideation to production. This includes data pipelining, feature engineering, model training, low-latency deployment, online A/B experimentation, and continuous performance monitoring for both predictive and generative models.
* Solve for Scale and Performance: Architect systems designed for the unique demands of a modern marketing platform--handling high-throughput traffic, low-latency serving for both ranking and LLM inference, and processing massive datasets.
 * Drive Technical Excellence for AI: Set the technical direction and establish best practices for blending traditional ML and generative AI within the marketing and CRM domains at Intuit. Act as a technical representative for AI/ML to the broader engineering and architecture community, guiding key decisions for how AI systems, processes, and capabilities develop.

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 [1] Intuit(R): Careers | Benefits).

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Qualifications

* A MS or PhD in a quantitative field (Computer Science, Physics, Statistics, etc.) or equivalent deep industry experience.
 * 10+ years of professional experience in applied AI/ML, with a proven track record of shipping and operating complex, large-scale machine learning systems in production.
* Deep Domain Expertise: Extensive, hands-on experience in large-scale ranking or recommendation systems. Direct experience in personalization or ad tech is essential, with a strong plus for experience in generative ads or applying LLMs to audience modeling.
 * Proficiency in Modern AI: Demonstrated experience applying Large Language Models (LLMs) to real-world business problems, including knowledge of techniques like RAG, fine-tuning, and building agentic workflows.
 * Hybrid AI science & ML engineering Skillset: You are both a strong modeler and a strong engineer. You have expertise in a wide range of ML algorithms and strong software engineering skills in languages like Python, Java, or Kotlin. 
* Technical Leadership: Demonstrated ability to lead complex technical projects and influence the roadmap of a cross-functional team.

 Preferred Qualifications

 AI:
 * Experience with multi-modal models for combined text and image ad generation.
* Deep familiarity with deep learning architectures for recommendation and ranking (e.g., Multi-Tower models, Transformers for sequence-aware recommendation, Multi-task NNs).
 * Experience building reasoning engines or conversational agents for complex tasks.

 ML:
* Deep familiarity with the infrastructure for serving LLMs at scale (e.g., vLLM, TensorRT-LLM).
 * Experience with real-time data streaming technologies (e.g., Kafka, Kinesis, Flink).
 * Experience building ML systems on a major cloud platform (AWS, GCP, Azure).

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: