Software Engineer, Context Engine

Sierra is the leading platform for customer-facing AI agents, partnering with major global brands including The Gap, Rocket Mortgage, SoFi, Sutter Health, and SoftBank to reimagine customer service and drive business growth. The company was founded by Bret Taylor, former co-CEO of Salesforce and CTO of Facebook, and Clay Bavor, who spent 18 years at Google leading Labs and overseeing AR/VR initiatives.

Sierra operates primarily from its San Francisco headquarters with expanding offices across North America, Europe, and Asia. The company is building the infrastructure and products that make AI agents increasingly intelligent and effective with each customer interaction. The engineering culture emphasizes trust, customer obsession, craftsmanship, and intensity balanced with a commitment to team wellbeing.

What you'll do

• Design and operate large-scale data systems handling terabytes or petabytes of data with low-latency requirements, working with technologies like Spark, Flink, Trino, and Iceberg-based data lakehouses.

• Build real-time eventing infrastructure, streaming and batch ETL pipelines, and data platforms that enable interactive OLAP querying, orchestration, and experimentation across the organization.

• Develop memory and personalization systems that power intelligent agent experiences, including long-term memory architectures and Customer Data Platform primitives.

• Create optimization loops that enable agents to personalize interactions and demonstrably improve business outcomes from millions of conversations.

• Architect systems for data governance, lineage tracking, and testing that are cost-conscious, highly operable, and intuitive for other engineers to build upon.

What you'll bring

• Four to seven-plus years of hands-on experience designing, building, and shipping production data systems or products at scale.

• Strong backend and distributed systems fundamentals in languages like Go, Scala, or Python, with deep understanding of storage engines, query optimization, and data serialization approaches.

• Expertise in data modeling best practices including dimensional modeling, star and snowflake schemas, and optimization for modern cloud data warehouses or traditional OLAP systems.

• Demonstrated ability to translate complex business questions into clear, usable interfaces with strong product instincts around information architecture and data exploration.

• High agency and bias toward action in autonomous environments, paired with genuine passion for frontier AI products.

• Computer Science degree or equivalent professional experience.

Nice to have

• Production experience with event streaming platforms such as Kafka or Kinesis.

• Familiarity with modern data visualization libraries like ECharts or D3.js and ability to build performant reusable charting components.

• Background with recommender systems or optimization techniques including multi-armed bandits and ranking algorithms.

• Track record leading complex technical projects or mentoring engineers.