Staff Full-Stack Engineer: Backend & AI Platform

Rippling

San Francisco (CA)

On-site

USD 189,000 - 315,000

Full time

5 days ago
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Job summary

Rippling is hiring a Staff Software Engineer to lead the Agentic Talent platform. You will build intuitive, secure, and scalable systems enabling AI-assisted talent workflows.

Collaborate with Product and AI Platform leadership to shape the vision, prototype ideas, and deliver category-defining products for a fast-growing enterprise software company. As an early member, you will shape technical direction, mentor engineers, and own critical software throughout its lifecycle, balancing ambiguity

Qualifications

  • 8+ years of full stack software development experience.
  • Experience with Python, Django, PostgreSQL, MongoDB, and React is strongly preferred.
  • Strong fundamentals in distributed-system design, asynchronous processing, caching, and data modeling.
  • Ability to design extensible services and APIs used across multiple products.
  • Proven track record of technical leadership and mentoring engineers.

Responsibilities

  • Build scalable, high-performance talent products and workflows.
  • Lead architectural decisions across the product lifecycle from prototype to production.
  • Own observability, reliability, and incident response standards.

Skills

Full stack development
Distributed systems
Product judgment
Leadership
Ambiguity navigation

Education

Bachelor's degree in Computer Science or equivalent

Tools

Python
Django
PostgreSQL
MongoDB
React
Event-driven architectures

Job description

Rippling is hiring a Staff Software Engineer to lead the Agentic Talent platform. You will build intuitive, secure, and scalable systems enabling AI-assisted talent workflows.

Collaborate with Product and AI Platform leadership to shape the vision, prototype ideas, and deliver category-defining products for a fast-growing enterprise software company. As an early member, you will shape technical direction, mentor engineers, and own critical software throughout its lifecycle, balancing ambiguity

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