Member of Technical Staff, Perplexity
Software Engineer, Data Platform
$220-405k
Offers Equity
Conversational AI-powered search tool
Open for applications
Conversational AI-powered search tool
1001+ employees
Open for applications
$220-405k
Offers Equity
1001+ employees
Company mission
To advance the way people discover and share information.
Role
Who you are
- 5+ years (Senior) or 8+ years (Staff) of software engineering experience
- Strong experience building production data infrastructure systems
- Hands-on experience with batch and/or streaming data processing at scale
- Deep familiarity with data orchestration systems (Airflow, Dagster, or similar)
- Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.)
- Strong systems thinking around reliability, latency, cost, and complexity tradeoffs
- Experience supporting ML/AI workflows, training pipelines, or evaluation systems
- Familiarity with data quality, lineage, observability, and governance tooling
- Prior ownership of internal platforms used by many teams
- If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above
What the job involves
- The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake
- The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse
- In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem
- Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation
- Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation
- Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows
- Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences
- Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction
- Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams
- Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap
- Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration
Our take
As AI continues to drive changes in both business operations and day-to-day lives, Perplexity delivers an intelligent search engine powered by conversational AI, to improve search outcomes and "unlock the power of knowledge" for all.
Reaching impressive heights of 22M monthly visits, Perplexity's "ask anything" method of search is clearly a popular one. And what sets it apart from other search engines is in its answers, which are concise and fully cited, responding to the user query rather than simply providing a place in which they can scroll to find it themselves.
The company has raised substantial funding, with contributions from former execs at companies like OpenAI, Meta, and Quora, demonstrating the interest that it has drummed up in the space. Having doubled its annual recurring revenue between 2023 and 24, this investment has allowed Perplexity to continue building out its product, and accelerate growth into the future.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 9 rounds)
Sep 2025
$200m
LATE VC
Jul 2025
$100m
LATE VC
Total funding: $1.8bn
Company HQ
Financial District, San Francisco, CA
Leadership
Aravind Srinivas
(Co-Founder, President & CEO)Former Research Scientist at OpenAI, who has interned in Research at Google and Deep Mind. Obtained a PhD in Computer Science from the University of California, Berkeley.
Denis Yarats
(Co-Founder & CTO)Prior to co-founding Perplexity in 2022, Denis was an AI Research Scientist at Facebook AI Research, a Staff ML Engineer at Quora, and a Software Development Engineer at Microsoft.
Johnny Ho
(Co-Founder & CSO)Previously a Quantitative Trader at Tower Research Capital, and Engineer at Quora.
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