Freelancer profile translated to English.
Back to original languageAbout Clément
AI Engineer & Cloud Engineer | RAG · LLM · FinOps · GCP/AWS ⚙️
You want to deploy aRAGsystem orLLMagents into production, but the infrastructure required to run them – and the associatedGCPor OpenAI bill – is holding you back?
Work with an engineer who wears both hats: I design your AI systems (RAG, agents, multi-model gateway, Vertex AI) AND the cloud architecture to industrialize them — deployment, scalability, security, and costs controlled onGCP / AWS.
Here's what my clients have achieved:
Club Med: Generative AI platform (RAG, multi-agents, LLM gateway via LiteLLM, LangChain, Vertex AI) in production for 2 years for Global Marketing —-50% GCP cloud costs.
Pass Culture: FinOps and cloud infrastructure redesign on BigQuery and Kubernetes —-54% storage and -86% infrastructure.
namR: ML inference infrastructure optimization on GCP (GKE, Terraform) —-80% inference costs.
Livetrend: Multi-cloud GCP ↔ AWS architecture (VPN, inter-cloud network) validated in production.
Based on your constraints (volume, latency, retrieval quality, cloud budget), I structure your AI stack and its accompanying infrastructure — RAG, agent orchestration, multi-model gateway, Terraform IaC, Kubernetes,FinOps, andMLOps.
You lead a B2B micro, small, medium, startup, or scale-up company and want to integrate AI into production without exploding your cloud bill — that's exactly my area.
An LLM/RAG system to industrialize or cloud infrastructure to stabilize and optimize? Click "Contact" and describe your situation in 3 lines, I'll respond within the hour with an initial analysis.
French
Native or bilingual
English
Native or bilingual
Can work on-site
Paris (up to 50km), Bordeaux (up to 50km), Lyon (up to 50km), Nantes (up to 50km), Marseille (up to 50km)
Experience
- Club MedAI Engineer & Cloud Engineer | RAG, Multi-AgentsENTERTAINMENT AND LEISUREMay 2023 - June 2025 (2 years and 1 month)Paris, France🎯 Mission ObjectiveDesign and deployment, over 2 years, of a generative AI backend platform for Club Med's Global Digital & Technology Marketing: document ingestion, full RAG, multi-agent orchestration, multi-model LLM gateway (LiteLLM), exposure of data via internal APIs, and automation of scalable cloud infrastructure with a FinOps approach.🔧 Achievements
- Design and deployment of acomplete generative AI platform: document ingestion, full RAG, multi-agent orchestration, and multi-model LLM gateway viaLiteLLM—2 years in productionwith the Global Marketing teams.
- LLM monitoring and observability (Langfuse): tracking costs, latencies, generation quality, and detecting production drift.
- Development ofPython / FastAPIAPIs to provide self-service data to business teams — containerized backend services, continuously deployed on the cloud.
- FinOps strategy for the GCP scope:-50% cloud costswithout service degradation, including optimization of LLM inference costs (caching, batching, task-calibrated models).
- Automation of cloud infrastructure with IaC (Terraform) and industrialization of CI/CD pipelines.
🧰 Technical Stack*Backend: Python (FastAPI, uv, Streamlit), SQL, Bash*Generative AI: LiteLLM, LangChain, ChromaDB, Vertex AI, Flowise, Langfuse*Cloud & Data: GCP (BigQuery, Dataform, Cloud Run, Vertex AI, Workflows, CloudSQL)*Containerization: Docker, Docker Compose, Ansible*IaC & CI/CD: Terraform, GitLab, GitHub - Livetrend.coCloud Engineer | Multi-Cloud GCP/AWS & PostgreSQLFASHION AND COSMETICSMarch 2025 - May 2025 (2 months)Paris, France🎯 Mission ObjectiveEvaluate AlloyDB (GCP) as a cost-effective alternative to Aurora (AWS) for Livetrend.co (B2B e-commerce) by replicating a realistic multi-cloud production setup, redesigning inter-cloud connectivity, and adapting backend jobs to ensure fair comparisons.🔧 Achievements
- Operational inter-cloud network architecture (high availability VPN + BGP routing) to secure backend traffic between GCP and AWS
- Deployment of a managed AlloyDB cluster equivalent to Aurora for benchmarking with an iso-configuration
- Adaptation of backend ETL jobs (orchestrated via Prefect) to run in the new VPC + interaction with AlloyDB
- Resolution of backend network issues (DNS, inter-VPC mounting, EFS replication) to ensure reliable data ingestion
- Validation ofAlloyDB for productionwith a better performance/cost ratio + identification of blocking points for large-scale migration
🧰 Technical Stack*Backend Data: PostgreSQL (AlloyDB, Aurora)*GCP Cloud: AlloyDB, Cloud VPN, Cloud Router, VPC*AWS Cloud: ECS, EFS, Aurora PostgreSQL*Network: HA-VPN, BGP, Site-to-site VPN, VPC Peering*Orchestration: Prefect - REWARDPULSEBackend Engineer & Cloud Engineer | NestJS, GCP & TerraformSOFTWARE PUBLISHINGNovember 2025 - May 2026 (6 months)Paris, France🎯 Mission ObjectiveIndustrialize the B2B multi-tenant loyalty platform RewardPulse (SaaS, GCP/NestJS): refactor a monolith into autonomous modular services, consolidate into a monorepo, replace no-code tooling, and fully secure the delivery pipeline.🔧 Achievements*Monorepoconsolidation (10+ services, 15+ shared packages) with incremental build and automated quality pipeline
- Refactoring into modularmicroservices(Notification Gateway, Transactional Outbox, Bounded Context layout), communication via Pub/Sub
- Shared library forpartner integrations(SFTP/API, retry, normalization),onboarding a partner in a few days
- Custom backoffice (SSR TypeScript, HttpOnly auth, multi-tenant RBAC) replacing a no-code solution
- GCP Terraform infrastructure (review apps, WAF, parallel DAG CI/CD) + security (Workload Identity Federation, PAM, audit logging)
🧰 Technical Stack*Backend: NestJS, TypeScript, Prisma, Drizzle, oRPC, Zod*Architecture: Microservices, Pub/Sub, Outbox Pattern*Frontend: TanStack Start (SSR), React, Vite*Cloud: GCP (Cloud Run, Cloud SQL, Pub/Sub, BigQuery, GCS, IAM)*IaC: Terraform, Terraform Cloud*CI/CD: GitLab CI, review apps
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Education
- Engineering Degree, GeneralistEcole Centrale de Marseille2022Diplôme d'ingénieur, Généraliste