You will own the quality measurement, testing, and improvement processes for AI products by building evaluation frameworks and automated tests. You will collaborate with engineering and product teams to identify failure patterns in AI systems and implement measurable improvements.
You will own the retrieval layer of a production AI platform, managing document ingestion, chunking, and embedding processes. The role involves building and optimizing agentic retrieval systems to ensure accurate and reliable information retrieval at scale.
You will build production AI features end-to-end, taking them from initial concept through to deployment. This involves working across the full stack, including API design, data integration, and creating streaming interfaces for document-heavy UIs.
You will take ownership of the backend infrastructure, building APIs and data pipelines that connect AI products with LLMs. This involves managing retrieval, tool-calling, response streaming, and complex background processing tasks.
You will take ownership of the infrastructure behind a production AI platform, focusing on scalability, reliability, and security. You will influence key architecture decisions and manage the deployment of AI workloads in production environments.
