Freelancer profile translated to English.
Back to original languageAbout Thomas
With 25 years of expertise in systems and network administration (Linux, databases, Kubernetes orchestration), I am now dedicated to implementing generative AI infrastructures, specializing in the deployment and optimization of LLM models locally (on-premise) or hybrid (cloud).
I offer a turnkey solution for companies wishing to:
✅ Deploy local LLMs (Mistral, Llama, etc.) or cloud (OpenAI, Anthropic, etc.) via a unified architecture based on an OpenAI-compatible proxy (LiteLLM).
✅ Centralize access to models through user interfaces (LibreChat, Open WebUI, or custom interfaces like chainlit) or directly via API, with quota management, logging, and monitoring.
✅ Secure and optimize costs by combining open-source models (self-hosted) and cloud services, according to business needs.
Why choose this approach?
- Data Sovereignty: Local hosting of sensitive models.
- Flexibility: Seamless switching between local and cloud models.
- Controlled Cost: Resource optimization (GPU, inference servers).
- Compatibility: Native integration with existing tools (standard OpenAI API).
Technical Environment:
- AI Infrastructure: LiteLLM (proxy), LibreChat, Ollama, vLLM, FastAPI, LangChain, chainlit.
- Models: Mistral, Llama, Mixtral, Phi-3, as well as cloud APIs (OpenAI, Anthropic, etc.).
- DevOps/Orchestration: Kubernetes, Ansible, GitLab CI, Terraform.
- Databases: PostgreSQL, Vector DB (Weaviate, Qdrant, PGVector).
- Historical Foundation: Linux (all distros), Oracle, MariaDB/Galera, JBoss, Tomcat.
At your service for:
- Auditing your generative AI needs (use cases, technical/regulatory constraints).
- Designing a suitable architecture (full on-premise, hybrid, or cloud).
- Supporting your teams in the use and administration of LLMs.
French
Native or bilingual
English
Native or bilingual
Can work on-site
Plaisir (up to 50km), Plaisir (up to 40km), Paris (up to km)
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Education
- Management Information Systems BTSPau1999Spécialisation Systèmes & Réseaux