Senior Staff Applied AI Engineer - Context Retrieval
Core
Building the zero-to-one retrieval stack and search subagents that power Databricks agents to retrieve and reason over context from Enterprise SaaS data.
Role type
Senior Staff Applied AI Engineer (Information Retrieval & Agentic Systems)
Builds
End-to-end retrieval infrastructure (query/content understanding, indexing, ranking) and agentic search layers for Databricks agents.
Domain
Enterprise SaaS data, Information Retrieval, Agentic AI
Deliverable
production ML models | product features
Required skills
Information Retrieval (IR), RAG architectures, agentic system design, relevance evaluation, hybrid retrieval, query understanding, content understanding pipelines, technical leadership
Preferred skills
Enterprise SaaS retrieval experience, agentic systems background, open-source IR contributions, model fine-tuning
Technologies
BM25, Lucene/Elasticsearch/OpenSearch, FAISS, ScaNN, HNSW, cross-encoders, LLM-as-judge
Responsibilities
Design and build the full retrieval stack from scratch; develop search subagents for multi-hop retrieval and sufficiency checks; optimize retrieval for both LLMs and humans; build connectors for heterogeneous SaaS data; establish evaluation flywheels for retrieval and subagents; set technical direction and mentor senior engineers.
Seniority
Senior Staff, hands-on IC with strategic leadership