AI LLM Retrieval Engineer

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November 25

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Titan AI

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Building mobile RPG Games with AI ✨ Companions 🤖. First game: Hell Rush is coming in July 2024.

1 - 10 employees

📋 Description

• Architect and maintain client-specific and internal RAG pipelines, including embedding generation, document chunking, and metadata tagging • Collaborate directly with enterprise clients to assess data landscapes, retrieval requirements, and grounding needs • Select, test, and optimize embedding models (text, multimodal) for accuracy and efficiency • Design retrieval strategies (dense, sparse, hybrid) to maximize precision and recall • Establish and monitor evaluation metrics for retrieval performance (e.g., recall@k, MRR, nDCG) • Align retrieval structure, granularity, and metadata with reasoning workflows • Maintain documentation, schemas, and retrieval guidelines for internal and client teams • Stay current with advancements in vector databases, embedding models, and retrieval frameworks

🎯 Requirements

• Proven track record building and optimizing retrieval systems in production • Deep understanding of embedding models, indexing strategies, and ANN search • Experience with vector DBs (e.g., Pinecone, Weaviate, Milvus, Vespa, FAISS) • Strong proficiency in Python and familiarity with RAG frameworks (LangChain, LlamaIndex, Haystack) • Knowledge of relevance tuning, hybrid search, and retrieval evaluation • Experience working with graph databases (Neo4J, ArangoDB) • Strong communication skills for technical and client-facing collaboration

🏖️ Benefits

• Competitive compensation (salary + meaningful, pre-Series A equity) • Unlimited PTO • Medical, dental, and vision coverage (100% of employee premiums paid by Titan)