About Eliott
Je construis des systèmes GTM dopés à l'IA qui génèrent du pipeline à une échelle que la plupart des équipes pensent impossible sans 10x les effectifs.
Je suis le mage noir du GTM Engineering — et l'IA a multiplié les résultats par 10.
Chez Skello, j'ai repris un process 100% manuel (20h/semaine, <2 000 leads/mois). En moins d'un mois : pipeline automatisé de bout en bout. En 2 ans : 1 million de leads générés, 60 commerciaux alimentés en continu, 2 000 nouveaux clients signés, €250K/mois de nouveau MRR. En 2024, j'ai déployé des agents IA de préqualification — de vraies conversations automatisées à l'échelle sur des centaines de milliers de contacts. Le code tourne encore aujourd'hui.
Chez Alma, je pilote l'intégralité du GTM stack — inbound et outbound. J'ai unifié 3 outils d'orchestration en pipelines Cargo , nettoyé 400K records HubSpot, construit un modèle TAM/SAM dynamique pour le dispatch commercial à travers toute l'Europe, et déployé un module de monitoring du churn à base d'IA.
Chez Lite : ×2 sur le volume de rendez-vous qualifiés en 3 mois.
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Mon approche : ship vite, mesure ce qui compte, itère sans relâche. ROI-first, toujours.
Ce que je construis :
• Clay + Cargo : sourcing, enrichissement IA, scoring, routing inbound + séquences outbound
• Agents IA : préqualification, personnalisation à l'échelle, détection de signaux
• Data pipelines : Airflow, Snowflake, AWS/GCP, DBT, Docker
• CRM : restructuration HubSpot/Salesforce, TAM/SAM dynamique, prévention churn
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Vous voulez doubler vos rendez-vous qualifiés avec Clay et Cargo ?
C'est exactement pour ça que vous m'appelez.
Full remote · Paris → Barcelone · Disponible 7j/7
French
Native or bilingual
English
Fluent
German
Conversational
Spanish
Basic
Can work on-site
Paris (up to 50km)
Experience
- AlmaGrowth EngineerBANKING AND INSURANCEFebruary 2025 - Today (1 year and 4 months)Paris, FranceOwns the full GTM stack at Alma — inbound and outbound, from first touch to territorial dispatch.Joined to untangle years of accumulated stack debt left by 5 successive teams: no documentation, no handover, 3 overlapping orchestration tools doing the same job badly.→ Migrated the full growth infrastructure from AWS to GCP with Terraform→ Rebuilt HubSpot from scratch: cleaned and re-enriched 400K records, restructured all properties, workflows and pipelines→ Unified n8n, HubSpot Workflows and Captain Data into a single Cargo orchestration layer — covering both inbound routing and outbound sequences→ Built a dynamic TAM/SAM model — live visibility on addressable market by territory, driving sales team structuring and dispatch across Europe→ Rebuilt end-to-end demand generation pipelines: inbound lead routing and qualification + outbound sourcing, enrichment and sequencing→ Shipped an AI-powered churn monitoring module: detects merchants connecting competitor platforms, auto-triggers AM alerts for retention interventionStack: Python, Cargo, Clay, HubSpot, GCP, Terraform, SQL, LaGrowthMachine, n8n
- LiteGrowth EngineerENERGY AND UTILITIESDecember 2024 - September 2025 (9 months)Paris, FranceEmbedded GTM engineering mission — CRM restructuring and full-funnel pipeline performance.→ Full HubSpot audit, cleanup and restructuration→ Rebuilt the client acquisition pipeline with AI-powered enrichment and scoring→ Doubled qualified meeting volume within 3 months→ Managed a growth apprentice for 6+ months on stack evolution→ Worked directly with Head of Sales, CEO and Head of MarketingStack: HubSpot, Clay, Cargo, LaGrowthMachine, SQL
- SkelloGrowth EngineerSOFTWARE PUBLISHINGOctober 2022 - August 2024 (1 year and 10 months)Paris, FranceTook over a 100% manual lead generation process (20h/week, <2,000 leads/month) and turned it into a fully automated, AI-powered GTM machine.→ End-to-end automated pipeline shipped within the first month→ 1,000,000 outbound leads generated over 2 years — feeding a 60-person sales team non-stop→ Contributed to 2,000 new customers signed and €250K/month in new recurring revenue→ Built and maintained 15+ Airflow DAGs on Kubernetes clusters — collection, enrichment, scoring, CRM delivery→ Siretization algorithm for French business data qualification at scale→ 2024: deployed AI pre-qualification agents — automated real conversations across hundreds of thousands of contacts in France→ Iterative approach throughout: ship fast, measure, improve. Each pipeline version more efficient than the last.→ The system still runs in production todayStack: Python, Airflow, Kubernetes, AWS (S3/Lambda/EC2/RDS), Snowflake, Docker, SQL, DBT, Looker, Salesforce, Terraform, AI agents, CI/CD
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Education
- Expert en Technologie de l'information et du numériqueEpitechFormation de développeur axée sur l'innovation, l'internationalisation et l'entreprenariat