Senior Staff Applied AI Engineer - Context Retrieval

📋 Description

• Build the end-to-end retrieval stack for Databricks agents.
• Index and rank across structured and unstructured data.
• Create connectors for enterprise data sources with fresh signals.
• Design subagents to reason about what context is needed.
• Optimize retrieval for both LLMs and human users.
• Set technical direction and mentor senior engineers.

🎯 Requirements

• 10+ years of software engineering with production retrieval or search at scale.
• Deep Information Retrieval expertise: lexical, dense, hybrid.
• Hands-on modern LLM-era retrieval: RAG, query rewriting, grounding.
• Experience designing agentic systems atop retrieval: planners, multi-hop.
• Strong relevance evaluation: nDCG, MRR, Precision@K, Recall@K.
• Experience across structured and unstructured data; built 0→1 retrieval systems.

🎁 Benefits

• Foundational impact: retrieval drives agent quality.
• Greenfield with enterprise scale: clean sheet with real data.
• World-class team across Lakehouse, Spark, Delta Lake, MLflow.
• Hybrid in-office work: Mountain View or San Francisco.