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Sierra is a leading platform for customer-facing AI agents, working with major brands including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank. The company is headquartered in San Francisco with growing offices across North America, Europe, and Asia.
You'll join a full-stack data team building systems that make AI agents measurably smarter with every interaction. The role spans two core areas:
Data Foundations: You'll architect and build the core platform to handle data at scale with low latency. This includes real-time eventing infrastructure, streaming and batch ETL pipelines, and an Iceberg-based data lakehouse. You'll own systems for interactive OLAP querying, orchestration, and experimentation, ensuring data is trustworthy, fast, and easy to use across the organization.
Memory & Personalization: You'll power the next generation of intelligent experiences by developing systems for long-term agent memory, building reusable Customer Data Platform (CDP) primitives, and implementing optimization loops that allow agents to personalize interactions and demonstrably lift business outcomes.
The role offers two specialization tracks:
Platform Engineering: Design, build, and operate large-scale data systems processing terabytes or petabytes using technologies like Spark, Flink, Trino/Presto, and data lakehouse formats (Iceberg, Hudi). Strong backend and distributed systems fundamentals in Go, Scala, or Python. Experience with data governance, lineage, testing, and data modeling best practices (dimensional modeling, star/snowflake schemas, slowly changing dimensions). Build cost-aware, highly operable platforms that delight other engineers.
Product Engineering: Ship data products including analytics dashboards, visualization tools, and alerting/exploration systems. Full-stack capability (TypeScript/React and service layer like Go) with strong performance and API design sensibility. Excel at turning ambiguous questions into clear, intuitive interfaces with strong product sense around information architecture and making complex data explainable. Practical experience with ML-powered product features such as personalization, recommendations, or classification systems.
Company values include Trust, Customer Obsession, Craftsmanship, Intensity, and Family. The company is primarily in-person based in San Francisco.
Requirements:
- 4-7+ years of hands-on development experience building and shipping production systems or products
- Strong software engineering background
- Degree in Computer Science or related field, or equivalent professional experience
- Passion for being on the frontier of AI products
- High agency and bias to action in high-autonomy environments
Preferred qualifications:
- Deep experience with event streaming platforms (Kafka, Kinesis) and real-time data processing
- Experience with modern data visualization libraries (ECharts, D3.js) and building performant, reusable charting components
- Production experience with recommender systems or optimization loops (multi-armed bandits, ranking)
- Track record of leading complex technical projects or mentoring other engineers
