Build AI agents that perform end-to-end data science workflows, including hypothesis formation, query execution, result interpretation, and recommendation drafting.
Build retrieval infrastructure and evaluation loops so AI systems can reliably query warehouse data, semantic context, and metadata.
Turn AI-assisted data workflows into reusable systems, tools, and patterns for the data team.
Automate the data lifecycle through self-healing pipelines, dbt model generation and validation, data-quality agents, and diagnosis workflows.
Build AI-powered experiment-analysis systems that interpret A/B tests, identify statistical issues and drivers, and draft ship/no-ship recommendations.
Create internal data products and self-serve AI interfaces that replace ad hoc stakeholder requests.
Own the full lifecycle from problem identification and LLM prototyping through evaluation, UX design, production launch, and quality monitoring.
Requirements
6+ years of experience in data science, analytics engineering, data engineering, or a related role.
Deep SQL skills and strong judgment around metrics, experiments, data models, and warehouse data.
Strong product sense and the ability to turn prototypes and stakeholder needs into adoptable products.
Hands-on experience building with frontier models, agents, RAG systems, evaluations, or AI-powered workflows.
Experience with dbt, warehouse schemas, data-quality issues, and durable data-system tradeoffs.
Ability to systematize manual processes, ship quickly, measure quality, and iterate autonomously.
Preferred: experience with production AI agents or agent-evaluation systems.
Preferred: experience with Snowflake, semantic layers, or metadata systems.
Preferred: experience building internal tools, Slack bots, CLIs, or developer productivity products.
Preferred: strong experimentation, metric-design, and statistical-interpretation experience.
Preferred: experience with BI tools and early-stage startups.
Benefits
High autonomy in defining and executing a new function.
Opportunity to build frontier-model and AI-native data systems at Perplexity.
Small-team environment with direct impact and minimal approval layers.
Systems are intended to multiply the output of the data team and stakeholders.
Salary: $175k - $330k/yr
Perplexity
The most powerful answer engine. Powering curiosity with answers backed by up-to-date sources. This is where knowledge begins.