François Aubert

– Built a scalable AI-driven dynamic pricing SaaS platform from scratch, now serving 20+ enterprise customers including multiple $1B+ revenue companies. – Led and grew a high-performing product-engineering team (20+ across 4 squads) by setting clear performance standards, implementing growth-oriented feedback systems, and fostering a culture of ownership, collaboration, and continuous learning. – Hands-on technical leadership with strong individual contribution across the entire stack: – Back: Python (Django), distributed services (Kubernetes, Redis, Celery, Lambda, SQS) – Front: TypeScript (React), TailwindCSS – Data: Designed, Implemented and maintained scalable ETL pipelines (Snowflake, SQL, S3, Step function, DBT, Dagster) processing pricing data at multi-terabyte scale – Infra: Led design and operations on AWS + EKS, scaling Kubernetes workloads and optimizing cost/performance across multiple services. Provisioned and managed environments using Terraform, including network, compute, and DB layers. Implemented SLO/SLA frameworks (Datadog) for business-critical services (Price API connected in real-time to customer websites). – Performance: High-concurrency environments. SLA 99.9% – ML: Designed ML pipelines (LSTM,GAM) and productionization efforts. – AI Stack: Developed autonomous Pricing Agents using LangGraph, Supabase, and LLMs (Gemini/Claude). – Owned end-to-end delivery of complex enterprise integrations via a dedicated team of Forward Deployed Engineers from scoping to deployment. – Led pre-sales engagements across Retail, B2B, Transportation and Rental industry, translating deep technical capabilities into compelling solutions, contributing to multiple seven-figure ARR client wins. – Drove and maintained SOC 2 Type II certification, leading all technical aspects of security and compliance across the company. – Building the next generation pricing platform. Involved in all the aspects of building from the ground up an AI-powered Data-Intensive SAAS.

– Built and improved reinforcement learning recommendation (RL) engine for major French companies. – Improved accuracy of proprietary bidding algorithm (multi-armed bandit). – Architected and deployed distributed real-time data pipelines (Kafka, Apache Storm, Cassandra) ingesting hundreds of events/sec, enabling sub-second bidding. – Automated deployment (Ansible) and managed cloud infrastructure (AWS)

– Delivered technical support and enhancements for enterprise software systems.

– Led the distribution of the products in New South Wales (~2000 packages per week) with increase in customers' basis (200% in 6 months). – Achieved 10% in cost savings thanks to dispatch and routes optimization algorithms.