On-Prem LLM & Vector DB Consultant
Work locations: Philadelphia | Work Mode: Hybrid, minimum 3 days in the office
Duration: 12 Months
About the Role
Consultant Requirements – On-Prem LLM & Vector DB Implementation
Core Experience
Hands-on experience deploying open-source LLMs such as Meta Llama 3 and Mistral / Mixtral in on-prem or private environments
Strong proficiency in Python for LLM inference, prompt engineering, and integration
Experience with CPU-based inference, model quantization, and performance tuning
Vector Databases & RAG
Practical experience with open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector
Proven implementation of Retrieval-Augmented Generation (RAG) pipelines
Experience generating and managing embeddings and metadata filtering
Security & Governance
Understanding of data privacy, air-gapped deployments, and enterprise security requirements
Experience implementing access controls and audit logging
Nice to Have
Experience with LangChain or LlamaIndex
Exposure to Rust, Go, or C++ for high-performance services
Familiarity with Docker and Kubernetes for on-prem deployments
Knowledge of inference frameworks (e.g., vLLM, llama.cpp, Hugging Face Transformers)
Prior work in regulated or enterprise environments
Deliverables
Reference architecture and deployment guidance
Working prototype (LLM + vector DB + RAG)
Documentation and knowledge transfer to internal teams
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