Software Engineer, Agent Data Platform

Requirements

• ABOUT US At Sierra, we’re creating a platform to help businesses build better, more human customer experiences with AI.
• Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook.
• Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens.
• Before that, Clay led the product and design teams for Google Workspace.
• WHAT YOU'LL DO You’ll join a full-stack data team building the systems making our AI agents measurably smarter with every interaction, building the real-time pipelines, analytics products, and deep personalization primitives that turn millions of conversations into business outcomes.
• WHAT YOU'LL BRING We’re excited to meet candidates who bring depth in one of these areas: Platform Engineering - You have designed, built, and operated large-scale data systems, processing terabytes or petabytes of data with technologies like Spark, Flink, Trino/Presto, and data lakehouse formats like Iceberg or Hudi. - You possess strong backend and distributed systems fundamentals in a language like Go, Scala, or Python.
• You understand the trade-offs of different storage engines, query plans, and data serialization formats. - You have a history of implementing pragmatic data governance, lineage, and testing.
• You’ve built platforms that are cost-aware, highly operable, and a delight for other engineers to build upon. - You're well-versed in data modeling best practices (dimensional modeling, star/snowflake schemas, slowly changing dimensions) and know how to optimize analytical query patterns for both traditional OLAP systems and modern cloud data warehouses.
• Product Engineering - You have a portfolio of shipped data products, including analytics dashboards, data visualization tools, or alerting and exploration systems. - You are a skilled full-stack engineer (e.g., TypeScript/React and a service layer like Go), with a keen eye for performance, API design, and polish. - You excel at turning ambiguous questions into clear, intuitive interfaces.
• experience with ML-powered product features, such as personalization, recommendations, or classification systems.
• experience in building and shipping production systems or products. - A passion for being on the frontier of AI products. - High agency and a bias to action in a high-autonomy environment. - Degree in Computer Science or related field, or equivalent professional experience.
• experience with event streaming platforms (e.g., Kafka, Kinesis) and real-time data processing. -
• Experience with modern data visualization libraries (e.g., ECharts, D3.js) and the principles of building performant, reusable charting components for complex data. - Production