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# Staff Software Engineer, Full Stack - QuickBooks Capital & Lending

- **Company:** Intuit Inc.
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $202,500.0 - $274,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Software as a Service, Cloud Computing, Continuous Integration, Data Architecture, Database Design, Elasticsearch, NoSQL, Scrum Methodology, Software Architecture, QuickBooks (Software), Software Engineering, SQL Databases, Data Streaming, Systems Integration, TypeScript, Data Logging, Test-Driven Development (TDD), Spring Cloud, ReactJS, Large Language Models, Spring-boot, Generative AI, Backend, Kotlin, Kubernetes, Information Technology, Apache Kafka, Graphql, Front End Software Development, Microservices
- **Published:** October 6, 2026
- **Apply:** https://dejobs.org/x/x/9A64FE0B13464721B42C695F7511E0CB/job/

## About the Role

* 8+ years designing and developing online SaaS applications with full-stack expertise across front end and back end.
 * BS/MS in Computer Science or equivalent practical experience.
 * Strong back-end expertise in Java and/or Kotlin with Spring Boot (or comparable modern frameworks).
 * Strong front-end expertise with JavaScript, TypeScript, and React (or a comparable modern framework).
 * 5+ years building and consuming web APIs (REST, and ideally gRPC and/or GraphQL) and designing service interfaces.
 * Deep command of the full software development lifecycle and the software design and architecture process.
 * Experience with automated testing and Test-Driven Development (TDD), and with CI/CD pipelines.
 * Strong technical leadership: setting direction, running design reviews, presenting, and serving as the cross-functional go-to person.
 * Excellent communication skills - able to explain complex technical topics to technical and non-technical audiences alike.
 * Experience working in Agile/Scrum teams.

Preferred / nice-to-have

 * Cloud-native development on AWS with microservices, containers, and Kubernetes.
 * Experience with event streaming (Kafka), search (Elasticsearch), and SQL/NoSQL database design.
 * Hands-on experience building or integrating AI/GenAI capabilities (e.g., LLM prompting, retrieval, model integration) and monitoring them in production.
 * Experience with observability and instrumentation (metrics, logging, tracing) for production services.
 * Business acumen - strategic thinking and the ability to connect engineering decisions to customer and business outcomes.
 * A track record of building strong teams: setting and evangelizing a vision, facilitative leadership, and attracting and growing talent.

## Description

* Drive significant technical initiatives end-to-end and across every layer of the stack - from API and data design to front-end experience.
 * Architect and build scalable, secure, cloud-native applications and services that interoperate cleanly with the systems around them.
 * Stay hands-on - roughly 70% of your time is spent coding - while setting the technical direction for your team.
 * Act as the technical subject-matter expert: lead the design of complex features, mentor engineers, and lead a small team through hard programming and design problems.
 * Lead requirements gathering, technical design, and project and test planning.
 * Identify high-impact opportunities to apply AI - both to enhance our products and to accelerate our own engineering - and coach the team on using AI tools and techniques effectively and responsibly.
 * Take AI-powered features to production and evaluate their impact on performance and customer outcomes with the right metrics.
 * Champion engineering quality: automated testing, CI/CD, observability, performance, security, accessibility, and internationalization.
 * Communicate clearly through crisp technical docs and design reviews, and partner across product, design, QE, and other engineering teams to deliver results.
 * Own quality through the full lifecycle, resolving issues across QA, pre-production, production, and post-release.