Staff Software Engineer - Search Quality
Owns search quality across hybrid retrieval systems serving AI agents and human users. The role focuses on ranking, relevance evaluation, embeddings, and grounding RAG outputs across heterogeneous enterprise data.
About the job
Responsibilities
- Own search-result quality for AI-agent retrieval and human search experiences.
- Optimize hybrid retrieval combining keyword-based and semantic vector search.
- Fine-tune ranking models for human-readable results and LLM-ready context.
- Build guardrails and relevance scoring to keep AI outputs grounded in reliable information.
- Connect structured SQL data, unstructured documents, and real-time business metrics.
- Apply traditional information-retrieval techniques to retrieval-augmented generation (RAG).
Requirements
- Experience with Lucene or Elasticsearch, embeddings, and ranking algorithms.
- Understanding of search relevance and evaluation frameworks.
- Experience with human-in-the-loop and LLM-based evaluation.
- Knowledge of relevance metrics including nDCG, MRR, and Precision@K.
- Ability to work with information retrieval and RAG systems.
Benefits
- Comprehensive regional benefits and perks are offered.
Skills
Lucene, Elasticsearch, Embeddings, Ranking Algorithms, Information Retrieval, RAG, Ndcg, Mrr, Precision@K, SQL
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