Remote AI-Native Platform Engineer (Staff)

First American; United States; Remote; USD 149,000 - 198,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k plan

PTO / Paid sick leave

Employee stock purchase plan

Job summary

First American is seeking a Staff Software Engineer to provide technical leadership across multiple engineering teams, guiding architecture and reusable platforms. You will mentor engineers, partner with product, security, and AI practitioners to deliver AI-native software for the real estate industry.

The role emphasizes cloud-native design, scalable distributed systems, and production AI experiences, with an emphasis on reliability, observability, and governance.

Qualifications

• 8+ years of experience designing and building production software systems, including leading large-scale technical initiatives
• Deep experience in architecture across multiple teams and domains
• Strong cloud-native distributed systems experience
• Experience operating production AI systems and AI workflows

Responsibilities

• Lead cross-organization technical strategy and define architectural direction
• Build and evolve AI development practices and AI-powered products
• Define architecture for large-scale distributed systems and drive API, event-driven, and cloud patterns
• Raise the engineering bar by establishing standards and reviews
• Mentor senior engineers and technical leads across teams
• Drive operational excellence, observability, and cost governance
• Collaborate with engineering, product, security, and platform teams to translate strategy into scalable solutions

Job description

First American is seeking a Staff Software Engineer to provide technical leadership across multiple engineering teams, guiding architecture and reusable platforms. You will mentor engineers, partner with product, security, and AI practitioners to deliver AI-native software for the real estate industry.

The role emphasizes cloud-native design, scalable distributed systems, and production AI experiences, with an emphasis on reliability, observability, and governance.