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Rasamison StephenRS

Rasamison Stephen

AI Full-Stack Developer

€200/day
Paris, FR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Rasamison

I design and deploy AI systems in production — autonomous agents, RAG pipelines, backend APIs — with measurable results.
What I've delivered recently:

Real-time multi-agent system for a call center of 50 operators → -35% processing time, latency maintained < 200 ms
RAG pipeline on +10,000 legal texts → +40% accuracy vs classic search, FastAPI API < 300 ms
Application management deployed in production → -60% data collection time

What I can do for you:

Build an AI agent or chatbot connected to your data
Set up a RAG system on your internal documents
Create or optimize your backend APIs (FastAPI, NestJS, Express)
Automate your data workflows (scraping, ETL, pipelines)
Integrate OpenAI, Claude, Vertex AI, or open-source models into your applications
  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km)

Experience

  • Etech
    AI Engineer
    February 2025 - May 2026 (1 year and 3 months)
    Objective: assist operators in real-time — contextual response suggestion, automatic call summarization, and intelligent customer ticket escalation.
    ● Architected and end-to-end managed the multi-agent system, reducing processing time by 35%.
    ● Defined orchestration patterns with LangGraph (state graphs, specialized nodes) via gRPC and WebSocket, maintaining latency < 200 ms.
    ● Designed the hybrid dense/sparse search strategy in Qdrant and LLM context caching via Redis.
    ● Scalable deployment on GCP with Docker, zero downtime in production.
    ● Conducted training workshop at the client's site for operational teams to adopt and use the system.
  • Mission freelance
    AI Developer
    May 2025 - August 2025 (2 months)
    Tananarive, Madagascar
    Design and implementation of a RAG system
    • Automatic scraping of legal texts with SeleniumBase
    • Preprocessing and chunking of the corpus, then generation of embeddings using OpenAI text-embedding-3-small
    • Indexing of vectors in Qdrant, hosted on an OVH server, with management of persistence and scaling
    • Deployment of a FastAPI API served by Uvicorn offering an endpoint for queries in hybrid search mode (dense + sparse) via LangChain
    Technologies: LangChain, Qdrant, FastAPI, SeleniumBase, OpenAI, Docker
    FastAPI Qdrant OpenAI OVHCloud Langchain

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Education

  • Master in Computer Science
    National School of Informatics (ENI), University of Fianarantsoa
    2024
    Master en informatique
  • Bachelor in Computer Science
    National School of Informatics (ENI), University of Fianarantsoa
    2022
    Licence en informatique

Skill set

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