Member of Technical Staff, AI Products (Early Career)
Perplexity · San Francisco
About this role
## 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 these 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**. This is a **full-stack** role in the truest sense: no frontend/backend lanes, and no waiting for tickets. It’s for people who love to build and want the room to do it. ## What You Will Do - **Own a user-facing surface end to end**, from interaction and design through frontend, application logic, APIs, data models, and the search/model calls behind them. - **Ship to production continuously** (new engineers typically have code in front of users in their first week). - **Build with AI as a primary tool**—use agents and coding models aggressively to move faster, with sound judgment about when their output is wrong. - Turn **ambiguous product ideas into working prototypes**, then use real usage data and evals to decide what survives. - Raise the bar on **reliability, latency, and craft** for the surfaces you own. - Work directly with **designers, PMs, and research engineers** without unnecessary process in between. ## 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 you understand in depth, shipped side projects with actual users, meaningful open-source contributions, hackathon wins, or research you turned into working software. - Comfort with ambiguity and an instinct to start building **incrementally** rather than waiting for a spec. - Hands-on experience with **AI products**, with opinions about their rough edges and what that means for the product you’re building. ## Nice to Have - Experience with our stack: **React/Next.js, Python, Go, PostgreSQL, Redis, Docker, AWS** (not expected to know all on day one). - Experience building on top of **LLMs**: AI orchestration, RAG, evals, agents, tool use. - **Product taste**: can tell a good interface from a bad one and explain how to improve it. - A public track record we can read (e.g., **GitHub, technical blog, or a demo** we can try).
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