AI Context & Data Infrastructure Engineer

📋 Description

• Build the search and retrieval layer that puts the right context at every Townie's fingertips, the
• Combine lexical and semantic search and own the tradeoffs between them: vector vs. lexical
• Design the durable data model the assistant's work is built on, so context is relevant, fast, and
• Build and operate the pipelines behind it — realtime/streaming and batch — that keep the index
• Stand up the indexing and storage layer and keep it fast and reliable at scale: latency, cost
• Lay the groundwork for relating content by meaning across everything the assistant knows — the

🎯 Requirements

• Have significant, hands-on experience across lexical and semantic search components and approaches
• Have run large-scale data infrastructure, ideally both realtime/streaming and batch — pipelines
• Can make retrieval fast and cheap at scale, and reason about the latency, cost, and freshness
• Are a systems thinker comfortable in greenfield, where the foundation doesn't exist yet.
• Are excited to take these systems from rapid prototype to production scale.
• Bonus if you've worked on ranking/relevance, knowledge graphs, or retrieval for LLM or agentic