Freelancer profile translated to English.
Back to original languageAbout Julien
90% of AI PoCs die before production.
Causes: overly complex architecture, **explosive inference costs (OpenAI/Gemini)**, latency, and zero monitoring.
As an AI & Backend Engineer, I don't build disposable prototypes.I rebuild slow, costly, or unstable LLM pipelines to scale them in production.
I assist Startups & Scale-ups who are blocked on the technical execution and infrastructure of their AI projects.
► MY APPROACH:
Simplification.I remove unnecessary layers (e.g., replacing a complex RAG + Redis with an asynchronous Kafka pipeline + solid Prompt Engineering). I implement intelligent routing tocut your costs by 3xand trueLLMOpsfor complete observability.
► WHAT I IMPLEMENT (Stack & Expertise):
- **Backend & Infra**: Python, FastAPI, Pydantic v2, asyncio, Kafka, S3, PostgreSQL, Redis.
- **LLM Engineering**: LangGraph, Function Calling, Schema-first JSON, Prompt Engineering, Multi-model routing (Gemini 2.5, OpenAI).
- **LLMOps & Monitoring**: Token/cost tracking, Rate-limiting, DLQ, Prometheus, Grafana.
- **Deployment**: Docker, Kubernetes (K8s), AWS (EKS, Bedrock), vLLM, RunPod, CI/CD.
► TANGIBLE RESULTS:
- Extraction Pipeline(Scale-up SOLV): Replaced an unstable system with a minimalist Kafka architecture.50k+ docs processed, 99.2% success, API costs ÷3.
- AI Constraint Clustering**: Designed a **scalable hybrid algorithmwhere DBSCAN/K-Means failed semantically.
- Automation (Venio AI)**: **Production-deliveredagent platform via OpenAPI spec.
💡 "**Senior-level execution from day one** — cross-functional deliveries across backend, DevOps, and the entire AI stack." — Luca F. (CTO, Venio AI)
► TERMS:
• Full remote (EU Timezone) | 3-6 month missions | Immediate availability.
Shall we look under the hood of your LLM infra?Contact me.
French
Native or bilingual
English
Fluent
Spanish
Fluent
Can work on-site
Paris (up to 50km)
Experience
- SOLVProduction LLM EngineerOctober 2025 - Today (8 months)Bruxelles, BelgiumBelgian scale-up in stakeholder analytics & risk management for complex infrastructure projects.LLM Document Extraction Pipeline:Complete reconstruction of an unstable extraction pipeline (Redis + embeddings + RAG + premium models, crashing at 10+ docs) using a minimalist asynchronous Kafka system in Python/FastAPI.→ 50,000+ documents processed, 99.2% success, cost reduced by 3xConstrained Clustering Algorithm:Design and implementation of a hybrid algorithm: feature extraction via LLM (orientation, entities, nature) injected as penalties into the distance matrix before hierarchical clustering. Solved the limitations of two previous attempts (DBSCAN, HDBSCAN+K-Means).Multi-model Routing & LLMOps:Intelligent routing Gemini Flash ↔ Gemini 2.5 Pro (OpenAI fallback), selection based on complexity/cost. Production Prometheus/Grafana dashboards (p95 latency, costs, extraction density), rate-limiting, exp-backoff retries, DLQ.
- Venio AIAI EngineerFebruary 2025 - September 2025 (7 months)Reggio d'Émilie, ItalyStartup specializing in AI agent automation for non-tech companies.Conversational Agent Platform:Built a platform for LLM agents in Python/FastAPI: the system understands user needs in natural language, generates a suitable agent, and exposes a ready-to-use API endpoint. Automatic generation of agent tools from OpenAPI specs.Benchmarking & Deployment:Benchmarking suite (accuracy, cost, latency) to compare LLM models and prompts before production deployment. Automated Docker/Kubernetes deployments via GitLab CI/CD.
- ONECLICKHIREDFounderJanuary 2025 - September 2025 (8 months)AI SaaS: CV parsing + automated personalized outreach. Full stack built solo: React/TS, Fastify, PostgreSQL, Redis/BullMQ, Stripe.Multi-provider LLM integration (Gemini + OpenAI), reliable asynchronous jobs. 150 sign-ups.
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Education
- Engineer, AIEPITA2025Ingénieur, IA
- MPCPGE N.D. de Sion2022MP