I will implement rag vector search and ai semantic search for your ecommerce

V
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V
valhallasoft
Martin Poli
implement rag vector search and ai semantic search for your ecommerce
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implement rag vector search and ai semantic search for your ecommerce
Full Screen
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implement rag vector search and ai semantic search for your ecommerceimplement rag vector search and ai semantic search for your ecommerceimplement rag vector search and ai semantic search for your ecommerce

About this gig

Stop losing sales to bad search.


If your ecommerce search returns no results when shoppers type natural queries instead of exact SKUs, you are leaving money on the floor. I implement production-grade RAG and semantic search that understands intent, not just keywords.


Real result: I am currently leading the AI search migration for one of Latin America's largest retailers (200+ stores, 1M+ daily users, 50K+ products), replacing Google Search API with a RAG-based system projected to save $500K per year.


What you get:

  • Vector database setup (Pinecone, Weaviate, Qdrant, pgvector)
  • - Embedding strategy and model selection
  • - Hybrid search: keyword + semantic + reranking
  • - Production deployment with monitoring and fallbacks
  • - A/B testing setup to prove lift

Stack: Python (FastAPI), OpenAI / sentence-transformers, AWS, Docker, Kubernetes.


Why me: 10+ years building production backends at scale. Senior Platform Engineer with cross-team architecture ownership. I ship tested deliverables and document so your team owns the system after delivery.


Message me with your stack, catalog size, and what is broken about your current search. I reply within 1 hour with concrete next steps.

  • AI engine

    • GPT
    • Gemini
    • Bert

  • Programming language

    • Go
    • JavaScript
    • PHP
    • Python
    • TypeScript

Get to know Martin Poli

Martin Poli

Senior RAG and AI Search Engineer for Backend at Scale

  • FromUruguay
  • Member sinceMar 2020

  • Languages

    English
Senior Platform Engineer with 10+ years building production systems at scale. Currently leading platform infra and AI search for Argentina's largest retail chain (200+ stores, 1M+ users/day), replacing Google Search API with RAG-based semantic search across 50K+ products. What I do best: - RAG, embeddings, OpenAI/Anthropic/Bedrock - Vector DBs: Pinecone, Weaviate, Qdrant, pgvector - Backend at scale: Python, Go, Node.js, PHP 8 - AWS EKS, Karpenter, Terraform, multi-account IaC Have a search problem or an LLM pipeline that won't ship? Send me your stack.

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