Sierra is an AI startup that builds agentic platforms and tools to power AI-driven customer experiences and autonomous agents.
ABOUT US At Sierra, we’re creating a platform to help businesses build better, more human customer experiences with AI. We are primarily an in-person company based in San Francisco, with growing offices in Atlanta, New York, London, Paris, Madrid, Munich, Singapore, Tokyo, and Sydney. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. 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. You’ll work across these areas: - Data Foundations: Architect and build our core platform to handle data at scale with low latency. This includes our real-time eventing infrastructure, streaming and batch ETL pipelines, and our Iceberg-based data lakehouse. You will own the systems for interactive OLAP querying, orchestration, and experimentation, ensuring our data is trustworthy, fast, and easy to use for the entire organization. - Memory & Personalization: Power the next generation of intelligent experiences. You will develop the systems for long-term agent memory, build reusable Customer Data Platform (CDP) primitives, and implement the optimization loops that allow our agents to personalize interactions and demonstrably lift 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. You have strong product sense around information architecture, handling empty states, and making complex data explainable. - You have practical experience with ML-powered product features, such as personalization, recommendations, or classification systems. Shared Qualities - Strong software engineering background with 4-7+ years of hands-on development 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. EVEN BETTER... - Deep 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 experience with recommender systems or optimization loops (e.g., multi-armed bandits, ranking). - A track record of leading complex technical projects or mentoring other engineers. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions an