Description
We are seeking a full-time Member of Technical Staff, AI Products (Early Career - Industry) to join our team in San Francisco.
The successful candidate will be part of the Product Engineering team, responsible for owning a user-facing surface end-to-end, from interaction design and frontend to application logic, APIs, data models, and search or model calls.
Compensation
The compensation range for this role is $180K - $270K, with equity offered.
Benefits
Full-time U.S. employees enjoy a comprehensive benefits program including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more.
About the role
In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, through Search, Comet, and Computer. Product Engineering owns those experiences end-to-end, from the interface a user touches to the search and model calls behind it, on top of roughly 200M queries a day and a 200B+ URL index.
What you will do
- Own a user-facing surface end-to-end, from interaction design and frontend to application logic, APIs, data models, and search or model calls.
- Ship to production continuously, with new engineers typically having code in front of users in their first week.
- Build with AI as a primary tool, using agents and coding models aggressively to move faster.
- Turn ambiguous product ideas into working prototypes and use real usage data and evals to decide what survives.
- Raise the quality bar on reliability, latency, and craft for the surfaces you own.
- Work directly with designers, PMs, and research engineers without unnecessary process.
What we look for
- 1+ years of professional software engineering experience, or a track record of strong internships where you shipped production code at scale.
- Strong in at least one backend language, such as Python or Go, with real experience across services, APIs, and relational data modeling.
- Comfortable working in React and TypeScript on the frontend.
- Real evidence of building production work, shipped side projects, or meaningful open-source contributions.
- Comfort with ambiguity and an instinct to start building incrementally.
- Hands-on experience with AI products and opinions about their rough edges.
Nice to have
- Experience with our stack: React or Next.js, Python, Go, PostgreSQL, Redis, Docker, AWS.
- Experience building on top of LLMs: AI orchestration, RAG, evals, agents, tool use.
- Product taste and the ability to explain how to improve an interface.
- A public track record, such as GitHub, a technical blog, or a demo.