Staff Software Engineer: AI-Driven Permitting Platform

Pulley

San Francisco (CA)

On-site

USD 180,000 - 280,000

Full time

14 days+

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Job summary

Pulley in the San Francisco Bay Area is seeking a staff-level software engineer to build the product that gets stuff built. You will work closely with engineers, designers, and end-users to accelerate development and ship AI-driven experiences.

You will own problem areas, set technical direction, mentor engineers, and drive architecture from ambiguity to production, focusing on scalable systems and high-velocity delivery.

Qualifications

  • 8+ years of software engineering experience.
  • Owning a significant technical domain end-to-end: from problem to production ownership.
  • Fluency in modern full-stack development (TypeScript, React, Google Cloud).

Responsibilities

  • Own problem areas, not just features—define the technical direction for a domain spanning multiple product surfaces and carry it from ambiguity through architecture to shipped product.
  • Turn unstructured permitting documents and jurisdiction workflows into fast, reliable product experiences with AI at the core.
  • Build with AI agents as a daily practice—directing, reviewing, and shipping agent-driven work at high velocity while maintaining quality.
  • Make the technical bets that determine next year's capabilities and own their production consequences.
  • Multiply the engineers around you: set direction, mentor senior engineers, and accelerate the team through shared systems and standards.

Skills

Software engineering
End-to-end ownership
Full-stack development
AI / LLM features
Mentoring engineers

Tools

TypeScript
React
Google Cloud

Job description

Pulley in the San Francisco Bay Area is seeking a staff-level software engineer to build the product that gets stuff built. You will work closely with engineers, designers, and end-users to accelerate development and ship AI-driven experiences.

You will own problem areas, set technical direction, mentor engineers, and drive architecture from ambiguity to production, focusing on scalable systems and high-velocity delivery.

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