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# Principal Software Engineer

- **Company:** Intuit Inc.
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $261,500.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Batch Processing, Business Software, Software as a Service, Extract Transform Load (ETL), Distributed Systems, JSON, Python (Programming Language), Object-Oriented Software Development, Platform as a Service (PAAS), Scrum Methodology, Service Design, Software Engineering, Systems Integration, TypeScript, Web Services, Data Processing, Large Language Models, Multi-Agent Systems, Apache Spark, Generative AI, Pyspark, Kubernetes, Information Technology, Apache Kafka, Software Coding, Domain Driven Design
- **Published:** September 29, 2026
- **Apply:** https://intuit.avature.net/externalCareers/JobApplication?pipelineId=24120

## About the Role

BS/MS in Computer Science or related area

 - 8+ years of experience developing systems/software for large business environments

 - 5+ years of experience designing complex distributed systems, management products, or business applications (ERP, financials, or operations domains a strong plus)

 - Strong, demonstrated background in applied AI - both traditional ML and Generative AI. Hands-on development and production rollout of agentic experiences is a huge plus

 - Experience with modern AI/agentic building blocks: LLM APIs and orchestration frameworks, prompt and context engineering, RAG/retrieval, tool use and function calling, multi-agent architectures, and evaluation/guardrail frameworks

 - Strong design and coding skills in one or more of Java, Python, TypeScript; experience with REST/JSON service design

 - Strong OOD and service-oriented/domain-driven design principles, with ability to implement them in a language of choice

 - Strong experience leading design and implementation of robust and highly scalable web services

 - Experience with real-time (Kafka, Pub/Sub) and batch processing architectures

 - Background in data processing and data movement (e.g., Spark/PySpark, SageMaker, feature/vector stores) to power AI-driven experiences

 - Experience instrumenting, evaluating, and iterating on AI systems in production (offline evals, online experimentation, quality/safety monitoring)

 - Skilled in software development lifecycle processes; experience with SCRUM, Agile, and iterative approaches

 - Able to operate at highly varying levels of abstraction - from business strategy to product strategy to high-level and detailed technical design to implementation

 - Synthesize achievable solutions from diverse inputs, alternative sources (build/buy/partner), and complex data

## Description

Leverage the state of the art in AI and agentic technology to design and deliver AI-native product experiences for mid-market ERP customers

 - Shape and build the architecture of an AI-native ERP from the ground up - where agents, automation, and human collaboration are first-class design principles

 - Build AI-native workflows embedding AI-driven automation with seamless AI-to-human collaboration (human-in-the-loop, approvals, explainability)

 - Design AI-native intelligent systems that proactively capture data signals, prevent issues before they occur, automate processes, and improve decision making

 - Evaluate and apply emerging AI/agentic patterns (LLM orchestration, multi-agent systems, tool use, retrieval, evaluation frameworks) and set the technical direction for their adoption

 - Drive significant technology initiatives end to end and across multiple layers of architecture

 - Drive design and implementation of durable software solutions that solve critical customer problems in the mid-market segment

 - Make data-backed decisions and drive the right level of instrumentation, evaluation, and experimentation for AI-powered features

 - Deliver technical design and implement highly available, scalable, and secure services with excellent quality - including the reliability, safety, and observability standards required for production AI systems

 - Capture requirements and use cases in partnership with product and design

 - Partner with other groups both inside and outside of Intuit for cross-functional design, solution integration, and onboarding of SaaS/PaaS/web/mobile offerings

 - Recommend development best practices, tools, and paradigms - including AI-assisted development workflows

 - Actively stay abreast of AI/agentic, SaaS, and PaaS trends and standards; recommend best practices and share learning

 - Pursue and resolve complex or uncharted technical problems and share key learnings

 - Provide technical leadership and be a role model to software engineers pursuing a technical career path

 - Coach and mentor other engineers in AI-native development practices, process, and methodologies

 - Provide perspective on leading industry trends, recommendations on new and emerging technologies, technology prototypes, patent proposals, and engineering process improvements