Freelancer profile translated to English.

Description

Do you want to deploy generative AI in production, not just test a POC that will end up in the closet?

I design and deliver agentic systems (autonomous agents, RAG, AI automations) that actually run in production, on GCP. 3 years of experience, 3x Google Cloud certified, I handle the entire cycle: business needs framing, architecture, development, production deployment, and monitoring.

What sets me apart:

Many GenAI providers can create impressive demos. Few can make them production-ready, with security, monitoring, and scalable architecture. My dual data engineering + GenAI expertise fills this gap: I come from the world of production data (critical pipelines, zero downtime), so I don't design off-the-shelf agents; I integrate them into your existing technical and business environment.

Types of projects I can help you with:

- Automation of time-consuming business processes via autonomous agents (marketing, ad ops, customer service…)

- Orchestrated multi-agent systems (A2A, MCP) with content generation (text, image, video) and human validation

- Secure enterprise RAG (data anonymization, protection against adversarial prompts)

- Automated scoring and classification from unstructured data (text, image)

- Migration or redesign of data pipelines to prepare for AI use cases

Recent deliverables:

- 100% automated marketing pipeline (trend detection → content generation → publication), for a retail player

- Ad Ops automation agent eliminating a repetitive manual task

4 AI systems in production for a retail innovation hub (product content generation, quality scoring, visual search, secure customer service assistant)

Stack: Python, GCP (Vertex AI, Cloud Run, BigQuery), Gemini, Google ADK, A2A, MCP, RAG, Terraform.

English: Near-perfect professional

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

SFEIR
GenAI
RETAIL (LARGE RETAILERS)
March 2025 - Today (1 year and 5 months)
Lille, France
Senior GenAI consultant in SFEIR's Google Cloud practice, the go-to technical reference for Generative AI across the firm. Lead architect and developer on production agentic systems for France's largest retail groups, owning the full lifecycle from design to deployment. Conduct GenAI technical interviews, co-author RFPs, and build live demos for strategic pre-sales.
AI Agent Generative AI Python Google ADK Google Cloud
Chronodrive
GenAI Engineer & Lead Architect
RETAIL (LARGE RETAILERS)
February 2026 - June 2026 (4 months)
Lille, France
Architected and shipped an end-to-end autonomous multi-agent system that fully automates the marketing content pipeline (from trend detection to cross-channel social publishing), replacing a previously manual workflow.
– Designed agent topology: A2A protocol orchestrator, brand-compliance agent, Google Drive RAG retrieval layer, full CI/CD and Terraform IaC
– Built generative media agents using Imagen 3 (visuals) and Veo 2 (video), plus a strategy agent consuming real-time signals via MCP (Google Trends, YouTube Trends) with human-in-the-loop approval gates
Stack: Python
• · GCP (Vertex AI, Cloud Run)
◦ · Gemini
◦ · Google ADK
◦ · A2A
◦ · MCP
◦ · RAG
◦ · Terraform
◦ · GitLab
Python Google ADK Google Cloud Generative AI AI Agent
Valiuz
GenAI Engineer & Lead Architect
E-COMMERCE
December 2025 - Today (8 months)
Lille, France
Designed and deployed an agentic automation layer for Ad Operations, eliminating the team's most time-consuming manual process end-to-end.
– Autonomous campaign-proof agent: multi-device screenshot capture, metadata overlay (URL, timestamp), structured Google Drive archival, automated stakeholder email notifications
Stack: Python
• · GCP (Vertex AI, Cloud Run, Cloud Functions)
◦ · Gemini
◦ · Google ADK
◦ · RAG
◦ · Terraform
Python Google ADK Generative AI AI Agent Google Cloud