Staff AI Platform Architect & Tech Lead

Intuit, Inc.; Oakland (CA); Vor Ort; USD 203.000 - 274.000; Vollzeit

Zusammenfassung

Intuit, Inc. in Oakland is seeking a Staff Software Engineer to own the architecture and delivery of core Financial Assistant capabilities.

You will set technical direction across multiple workstreams and mentor engineers while partnering with product, design, data science, and platform teams to ship fast, reliable AI experiences. This hands-on role requires leading complex initiatives, writing production code, establishing best practices for LLM-powered features, and ensuring safety and

Qualifikationen

• 8+ years of software engineering experience
• Expertise in building and operating production services
• Experience with AI/ML-powered features and LLMs
• Strong system design and leadership capabilities
• Excellent communication with technical and non-technical partners
• Bachelor's or Master's degree in Computer Science or related field or equivalent experience

Aufgaben

• Own architecture and delivery of core Financial Assistant capabilities across multiple workstreams.
• Mentor engineers and raise the engineering bar while partnering with product, design, data science, and platform teams.
• Write, review, and elevate production code; establish patterns and best practices.
• Define and improve production AI practices: prompt design, evaluation, latency, cost, and safety guardrails.

Kenntnisse

Leadership

System design

AI/ML systems

Communication

Ausbildung

Bachelor's or Master's in Computer Science or related field

Tools

TypeScript

Java

Scala

Python

Jobbeschreibung

Intuit, Inc. in Oakland is seeking a Staff Software Engineer to own the architecture and delivery of core Financial Assistant capabilities.

You will set technical direction across multiple workstreams and mentor engineers while partnering with product, design, data science, and platform teams to ship fast, reliable AI experiences. This hands-on role requires leading complex initiatives, writing production code, establishing best practices for LLM-powered features, and ensuring safety and