Product Engineer

Product Engineer – Artie Salary: $150K - $215K • San Francisco, CA, US • Full-time • Will sponsor visa. About the role We're a small, dynamic team based in San Francisco, and we're looking for a founding engineer to join us. In this in‑person role, you'll have the opportunity to wear multiple hats, interact directly with our customers, and play a vital part in shaping the future of our product. This is a challenging and dynamic role where you'll be working at the forefront of distributed systems, infrastructure and data engineering. What you should expect and examples of day‑day tasks: Talking to customers (who are technical and have an engineering background) to streamline their workflows and improve the UX of our product Building new features into our product such as column exclusion, encryption, schema change alerts and more Improving our internal tooling and build automation to make it easier to ship features and manage our infrastructure About us Artie is a real‑time database replication solution for databases and data warehouses. We do this by leveraging Kafka and change data capture (CDC). We're growing fast - we launched our cloud product a year ago and have surpassed 1M ARR. We're backed by Pathlight Ventures, General Catalyst and other world class investors. What we are looking for Strong fundamentals in computer science or related field 4+ years of experience with web development and working at startups Pragmatic and care more about building the right thing vs. being right Comfortable jumping around the stack and wearing different hats Someone that is passionate about building products that are easy to use and extensible Proficiency writing in Go is preferred, but not necessary Happy to work in‑person 5 days/week in San Francisco’s Financial District with the rest of the team. Tech stack Frontend: TypeScript (React and Material UI) Backend: Go, PostgreSQL, Redis, Kafka and Elasticsearch Infra: Terraform, Kubernetes, and Helm on GCP and AWS About Artie We are building Artie, a real‑time data streaming solution focused on databases and data warehouses. Typical ETL solutions leverage batched processes or schedulers (DAGs, Airflow), which cannot achieve real‑time data syncs. We leverage change data capture (CDC) and stream processing to perform data transfers in a more efficient way, which enables sub‑minute latency. #J-18808-Ljbffr