🚀 Engineering Leader · Platform & Data · Staff Data Engineer @ Hydrosat
🧩 Ex-Kpler · Ex-Publicis  |  🌍 Paris, France  |  ☁️ Google Cloud Certified Professional Cloud Architect

Building AI & data platforms as products for engineers, and leading the teams behind them.

Engineering leader with 20+ years in engineering and 10+ managing high-performing teams. I build AI and data platforms as products for engineers, and the teams behind them. Hands-off on feature delivery, hands-on where it counts: architecture, system design, incidents, peer review.

Currently Staff Data Engineer at Hydrosat, building a next-gen data platform from scratch on AWS/Kubernetes with observability stood up from zero. Previously founded and ran the MLOps platform and squad at Kpler as it scaled from ~100 to 750+ people and past $100M ARR.

I pair platform & developer experience (APIs, internal tooling, CI/CD, observability) with MLOps to turn cutting-edge AI into reliable, production-grade systems at scale. Python and TypeScript. Low-ego, ship-early operator.

Code is like humor. When you have to explain it, it's bad. — Cory House

• Cloud: AWS (EKS, S3, Aurora, RDS, Redshift, Glue, Lambda), GCP (BigQuery, GCS, Cloud Functions, Composer)
• Kubernetes: EKS, Karpenter, VPC CNI (prefix delegation), Helm, ArgoCD
• IaC: Terraform / OpenTofu, CloudFormation, Ansible
• Containers & local dev: Docker, Colima, Nix
• FinOps: autoscaling to near-zero idle cost, right-sizing, cost observability

• CI/CD: GitHub Actions (reusable composite actions & workflows), CircleCI, ArgoCD (GitOps)
• Observability: OpenTelemetry, Grafana / Grafana Cloud, Prometheus, Datadog, Sentry, ELK Stack
• SRE: RED dashboards, distributed tracing, alerting, on-call, blameless post-mortems
• Testing: pytest, Jest, k6 (load testing)

• Orchestration: Apache Airflow (KubernetesPodOperator / KubernetesExecutor), Astronomer, AWS Glue, Cloud Composer
• Storage & databases: PostgreSQL (PostGIS), Aurora, BigQuery, Redshift, Elasticsearch, Redis, S3 / GCS data lakes
• Big data & streaming: Spark, Kafka, Cassandra
• BI: Tableau, Looker Studio

• Platform (built from scratch at Kpler): self-service GPU training, deployment & inference, model store, model monitoring
• Tooling: SageMaker, CI/CD pipelines for ML
• Frameworks: PyTorch, XGBoost, YOLOv8, Detectron2
• Vector search: Meilisearch

• Daily drivers: Claude Code, Codex, GitHub Copilot, Cursor
• Agentic practice: MCP, AGENTS.md, custom skills
• Prototyping: v0 by Vercel, Gamma

• Backend: Python (FastAPI), Node.js, GraphQL, Prisma, SQLAlchemy
• Frontend: TypeScript, React, Next.js, Vue.js, shadcn/ui, Radix UI
• Edge & BaaS: Vercel, Supabase

• Architecture: distributed systems, high availability, microservices, event-driven
• Practices: TDD, Clean Architecture, SOLID, SDLC, RFCs / technical writing
• Modeling: API design, UML, Merise

• 🏒 Ice hockey
• ⛷️ Alpine skiing
• 🎢 Roller coasters