Vector DB Engineer

Introduction:

ReEnforce is hiring for one of its Asset management/Hedge fund clients based out of NYC. We are looking for a highly competitive, top-notch candidate willing to work in a fast-paced environment.

Responsibilities:

• Design, develop, and maintain high-performance vector database systems (e.g., Pinecone, Weaviate, Milvus, FAISS, Qdrant) for LLM-backed applications.
• Integrate LLMs (OpenAI, Claude, LLaMA, etc.) into data pipelines and AI solutions using RAG and embedding-based retrieval.
• Build and manage embedding pipelines (using OpenAI, HuggingFace, SentenceTransformers, etc.) for structured and unstructured data.
• Optimize vector search for latency, relevance, and scalability across large datasets.
• Collaborate with ML/AI engineers, data scientists, and product teams to deliver end-to-end solutions powered by AI.
• Monitor performance, ensure data security, and maintain high system availability.
• Evaluate and experiment with different vector indexing techniques (e.g., HNSW, IVF, PQ) and distance metrics (cosine, Euclidean, dot-product).
• Stay updated with the latest advancements in LLMs, vector databases, and semantic search.

Requirements:

Required Skills:

• Experience with Vector Databases (Pinecone, Weaviate, Milvus, FAISS, Qdrant)
• Knowledge of Machine Learning (ML) and Artificial Intelligence

Preferred Skills:

• Experience with Pinecone, Weaviate, Milvus, FAISS, Qdrant
• Familiarity with RAG
• Previous experiance in Asset management/Hedge fund