Staff Software Engineer

Come join the QuickBooks Workforce Solutions engineering team at Intuit as a Staff Software Engineer. Our platforms power payroll and workforce experiences for millions of small businesses and the people who work for them, and they have to be fast, reliable, and correct at every scale. We are looking for an engineer who has designed and operated large-scale, highly available distributed systems, and who has built real AI/ML and agentic experiences in production, not just experimented with them. You will shape the technical direction of how our platform scales and how AI agents safely automate workflows for customers and internal teams, and you will help expose our capabilities to Intuit's AI assistants and partner agent platforms. Intuit acts as a 35-year-old startup, constantly disrupting ourselves to deliver on our mission to power prosperity around the world. This is a hands-on technical leadership role: you will write code, design systems, mentor engineers, and partner closely with product, design, and data science. Responsibilities Scalable system design •  Own the architecture of high-volume, high-availability services that handle peak loads with strict correctness, reliability, and latency requirements. • Design for correctness at scale: idempotency, data consistency, retries, and safe failure and recovery modes. • Drive event-driven and workflow-based architectures (Kafka, state machines, sagas) across distributed services. •Lead capacity planning, performance tuning, and resiliency engineering (multi-region, graceful degradation, load shedding). • Raise the operational bar through observability, SLOs, alerting, and incident prevention. AI/ML and agentic experiences •   Design and ship agentic workflows that automate complex, multi-step tasks for customers and operations teams. • Build the tool and API layer (for example, MCP servers and tool-calling interfaces) that lets LLM-based assistants securely read and act on product data. • Define guardrails for agents acting on sensitive data: authorization, human-in-the-loop checkpoints, policy enforcement, and auditability. • Establish evaluation, testing, and monitoring practices for LLM and agent behavior (offline evals, golden datasets, regression suites, production quality metrics), and partner with Responsible AI on review. • Partner with data science to bring ML capabilities such as prediction, anomaly detection, and personalization into production. •Use GenAI tools to accelerate engineering across the team, and build reusable components other teams can adopt. Technical leadership • Spend roughly 60-80% of your time hands-on: designing, coding, and reviewing. • Lead functional requirements, technical specifications, and test planning for major initiatives; accurately scope effort, identify risks, and communicate trade-offs. •Act as the technical go-to person for your area; diagnose and resolve complex, cross-system production issues. • Mentor engineers on technology, design, and operational excellence, and raise the team's skill in distributed systems and applied AI. •Influence product and technology direction with data; communicate clearly with senior product and business partners. Qualifications • BS/MS in Computer Science or equivalent work experience. • 8+ years of experience building systems and services for large-scale business environments (Java, Spring Boot); full-stack experience with React/JavaScript is a plus. •  5+ years designing, building, and operating robust, highly scalable, highly available distributed systems; you can walk through systems you designed, the scale they handled, and the trade-offs you made. • Strong command of distributed systems fundamentals: consistency models, idempotency, concurrency, partitioning, caching, and failure handling. • Practical experience with microservices and messaging technologies (REST, GraphQL, Kafka, Kubernetes, AWS). •  Strong database design experience across SQL (MySQL/PostgreSQL) and NoSQL (DynamoDB, Cassandr