Engineer at Intuit

Compensation

$202,500 – $274,000/yr

Setup: Hybrid
Location: Mountain View, California
Type: Full-time
Level: not_specified

Description

Join the QuickBooks Capital & Lending team to build cloud-native, AI-powered software for small businesses. You will architect and develop scalable applications, lead technical initiatives, and mentor a team. Focus areas include AI application, engineering quality, and seamless collaboration across various teams.

Required Skills

Java
Kotlin
Spring Boot
React
TypeScript
JavaScript
gRPC
GraphQL
API Design
Service Interfaces
Software Development Lifecycle
Automated Testing
Test-Driven Development
CI/CD Pipelines
Agile/Scrum Teams
AWS
Kubernetes
Kafka
Elasticsearch
SQL/NoSQL Database Design
Observability
Instrumentation

Additional Information

Minimum Education: BS/MS in Computer Science or equivalent practical experience.
Required Previous Experiences: 8+ years designing and developing online SaaS applications with full-stack expertise across front end and back end.
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 Qualifications: 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.