Principal Engineer - RAG Database & Embeddings Architect
Charlotte, United States
USD 140K-200K (estimate) Senior-level Full Time
Tasks
- Create reusable patterns reference architectures and standards
- Define embedding strategies
- Define observability for retrieval quality
- Define portfolio engineering approach
- Define solution technology tool stack
- Define vector schema standards and access control aware retrieval
- Design enterprise RAG data store architecture
- Design vectorization workflows including chunking and indexing
- Evaluate and select embedding models
- Implement semantic and hybrid retrieval patterns
- Lead end-to-end test strategy and integration
- Lead evaluation of vector database platforms and retrieval frameworks
- Lead portfolio feature design across teams
- Optimize retrieval using metrics and reranking
- Provide engineering leadership and mentoring
- Provide technical oversight and design reviews
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | Approximate Nearest Neighbor | Chunking | Database Design | Distributed Systems | Embedding Model | Embedding model evaluation | Embeddings | Hybrid retrieval | Indexing | Latency optimization | Metadata Modeling | Model Evaluation | Nearest neighbor | Observability | Performance Tuning | Precisión | Query Expansion | Recall | Reranking | Retrieval-Augmented Generation | Security Compliance | Semantic Search | Similarity Metrics | Vector Database | Vector Search | Vector schema
Education
Regions
Countries
States
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