About the Job
Yuki is a Tel Aviv-based startup building the optimization layer for modern data platforms. We help data teams cut Snowflake and BigQuery costs by automatically routing every query to the right compute in real time, with no code changes required. Our customers include companies like Zendesk, Tenable and Angel Studios, and we're backed by Hyperwise Ventures, VelocitX, Tal Ventures, and Fresh.Fund.
We're looking for a senior software engineer who can work across almost everything we build: the routing engine, the query proxy, the platform integrations and the customer app. Today we support Snowflake and BigQuery. We're starting to fit in Iceberg-based engines such as DuckDB and StarRocks, and we're expanding to Databricks soon.
We build with AI agents every day. We're looking for someone who does too, owns what ships, and makes the way we work with agents better.
What You'll Do
- Build across Yuki's products: Work on our query proxy (Go), our backend (C# / .NET), our AI infrastructure (Python), our platform integrations and our customer app (React / TypeScript), running on AWS and GCP with Kubernetes and Terraform.
- Own production: Our proxy sits between customers and their data warehouse. Latency, correctness and safe rollouts matter. You'll ship, monitor, and take your share of on-call.
- Build with AI, own the result: Use coding agents to move fast. Decide what they do, review what they produce, and stand behind it in code review and in production.
- Improve how we build: Help shape our agentic development process: review practices, guardrails, and the tools and context our agents work with.
What You'll Bring
- Experience: 5+ years building and running production systems.
- Cloud: Hands-on experience with AWS, GCP and/or Azure.
- Agentic development, with human judgment: You build with AI coding agents daily. You know how to give them context, verify their output and improve it, and you care about the process around them, not only the result.
Big Advantages
- Snowflake or BigQuery: Warehouse sizing, query profiles, credit and slot cost models.
- Databricks: SQL warehouses, Unity Catalog, Delta Sharing, Photon, serverless, DBU billing.
- Spark internals: Execution plans, shuffles, adaptive query execution, cluster sizing.
- Apache Iceberg: Table format, catalogs, and how engines read it.
- Data-oriented background: Experience at a data-oriented company, or in a data platform or data infrastructure department.
Why This Role
You'll work across the whole product at the layer where data platforms spend their customers' money, and you may take a new platform integration from zero to production. Most engineers join an integration after it exists. Here, you could be the one who builds it.
