Core Experience

• Hands-on experience deploying open-source LLMs such as Meta Llama 3 and Mistral / Mixtral in on-prem or private environments (25%)


• Strong proficiency in Python for LLM inference, prompt engineering, and integration (25%)


• Experience with CPU-based inference, model quantization, and performance tuning (25%)

Vector Databases & RAG

• Practical experience with open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector (25%)


• Proven implementation of Retrieval-Augmented Generation (RAG) pipelines (25%)


• Experience generating and managing embeddings and metadata filtering (25%)

Security & Governance

• Understanding of data privacy, air-gapped deployments, and enterprise security requirements (25%)


• Experience implementing access controls and audit logging (25%)

Nice to Have
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