Member of Technical Staff, AI Products (Early Career - Industry)
At a glance
Senior Software Engineering role at Perplexity. San Francisco · full-time · $180,000–$270,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Take a user-facing feature from interaction design through frontend, APIs, data models and search or model calls
- Put code into production continuously, turning rough product ideas into prototypes and improving them with usage data and evaluations
- Use AI agents and coding models to speed up development, while checking when their suggestions are unreliable
- Improve reliability, response time and implementation quality across the product areas you own
- Build directly with designers, product managers and research engineers
What you bring
- At least one year of professional software engineering, or substantial internships that included production software at scale
- You’re strong in a backend language such as Python or Go, with hands-on work across services, APIs and relational data
- You can build frontend features with React and TypeScript
- You can show shipped software through production work, projects with users, open-source contributions or another listed form of evidence
- You’ve worked with AI products and can discuss their limitations and how those shape product decisions
Who this fits
This early-career industry role suits a builder who learns quickly, handles unclear problems by making incremental progress and can work across the stack. You need to be working in software engineering already; new graduates and current students are directed to a separate program. The role is based in San Francisco.
From the employer
NOTE ON ELIGIBILITY: this role is for industry candidates already working in software engineering for the past 1+ years. New grads and current students should NOT apply to this role (instead, visit pplx.ai/newgrads).
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.
This is a full stack role in the truest sense. There are no frontend or backend lanes here, and no one waits for a ticket before starting. It suits people who love to build and want the room to do it. What you have shipped and how quickly you learn tell us far more than years on a resume or where you went to school.
What you will do
Own a user-facing surface end to end, from the interaction, design, and frontend through the application logic, APIs, data models, and the search or 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, not a novelty. We expect you to use agents and coding models aggressively to move faster, and to have 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 quality 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 wait for a spec.
Hands-on experience with AI products, with opinions about their rough edges and what that means for the product you are building.
Nice to have
Experience with our stack: React or Next.js, Python, Go, PostgreSQL, Redis, Docker, AWS. You will not be expected to know all of it on day one.
Experience building on top of LLMs: AI orchestration, RAG, evals, agents, tool use.
Product taste. You can tell a good interface from a bad one and explain how to improve it.
A public track record we can read, such as GitHub, a technical blog, or a demo we can try.
Software Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Software Engineering$180k+
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