Member of Data Staff (AI Builder)

Perplexity; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Perplexity is seeking a data-focused engineer to advance AI-driven analytics, building systems that turn data into actionable insights. You’ll work on end-to-end analysis workflows, from hypothesis formation to drafting recommendations with proper evaluation and guardrails.

The role emphasizes building AI systems that transform how data science is done, including retrieval and evaluation loops to support reliable warehouse queries and proactive data issue detection.

Qualifications

• Experience building AI-enabled data products and pipelines.
• Ability to design metrics that matter and run informative experiments.
• Familiarity with end-to-end analytics workflows and data quality guardrails.

Responsibilities

• Build AI agents and internal systems for end-to-end analysis workflows.
• Design retrieval infrastructure and evaluation loops for reliable data querying.
• Detect and diagnose data issues to prevent company-wide impact.
• Develop scalable data tooling and AI-native operating models.

Skills

A/B testing

Data modeling

SQL

AI systems

Job description

Perplexity is AI for people who expect more. This role brings that same standard to how our data team works, with AI at the center of everything we do.
We're looking for someone who's been a great data scientist, analytics engineer, or data engineer: the kind of person who knows which metric actually matters, can design an A/B test that answers the real question, has gone deep on a data model because something didn't add up, and has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done.
You'll build AI agents and internal systems that can increasingly handle end-to-end analysis workflows: forming hypotheses, writing and running queries, interpreting results, and drafting recommendations with the right evaluation, review, and guardrails. You'll build the retrieval infrastructure and evaluation loops that let AI systems query the warehouse reliably. You'll create workflows that detect, diagnose, and help fix data issues before they become company-wide problems. You'll build the infrastructure that multiplies what a small data team can ship.
You'll join a data team that's already using AI across its work. The next step is turning those individual workflows into scalable systems, shared tools, and an AI-native operating model that becomes a benchmark for how modern data teams work.
What You'll Do