Professional Summary
Cloud Developper specializing in generative AI systems, RAG developperures, and LLM orchestration. Experience designing and deploying production AI applications on AWS Bedrock and Google Vertex AI with Terraform and modern orchestration frameworks. Strong foundation in cloud infrastructure, vector databases, and DevOps practices. Open source contributor focused on advancing AI tooling ecosystems.
Professional Experience
- Developpered a multi-format document ingestion foundation for a RAG/GraphRAG knowledge base system, supporting diverse file types including video and legacy codebases (IBM i / AS400)
- Designed extraction pipelines to surface business and functional knowledge from legacy applications, enabling semantic retrieval over previously inaccessible enterprise assets
- Contributed to the global delivery plan for the GPAP modernization project at Desjardins
- Developed a documentation visualization tool to streamline Confluence page administration
- Designed CI/CD pipelines aligned with enterprise governance strategies
- Designed and implemented a RAG-based conversational AI system for personal data protection compliance
- Developpered the full AWS infrastructure and deployed the solution end-to-end using Terraform
- Built the frontend interface with Flutter, integrating Cognito-based authentication
- Managed DevOps developperure including Azure and AWS deployment pipelines
- Designed and optimized LLM orchestration for a generative AI chatbot within an AWS Landing Zone Accelerator environment
- Conducted R&D on orchestration techniques to reduce latency and improve chatbot response quality
- Implemented a test bench to track and measure conversational AI performance
- Trained the production support team on system developperure, troubleshooting, and maintenance
- Configured, deployed, and managed Azure cloud resources supporting ministry initiatives
- Performed in-depth performance analysis using Azure monitoring and logging tools
- Developed a pipeline variable analysis and optimization tool to eliminate redundancies between source code and IaC
- Configured access control strategies for solution versioning and deployment
- Maintained and developed core features for warehouse management and gas delivery tracking systems using C# .NET, Xamarin, and SQL Server
- Refactored the frontend codebase by 40%, resulting in 2–3x faster execution speeds
- Improved UI/UX across a dozen features in a Flutter application, collaborating in a multidisciplinary environment
- Maintained and refactored REST APIs leveraging a microservices developperure
Skills & Expertise
GenAI & ML
- LLM Orchestration
- RAG / GraphRAG
- AWS Bedrock
- Google Vertex AI / ADK
- LangChain / LlamaIndex
- Vector DBs (PGVector, ChromaDB, Neo4J)
- Langfuse / FMEval
Cloud & DevOps
- AWS (EC2, Lambda, Bedrock, S3)
- GCP (Vertex AI, Cloud Run)
- Terraform
- Docker
- GitHub Actions
- Azure
Development
- Python
- C# / .NET
- FastAPI
- Dart / Flutter
- pytest / CI/CD
Projects & Open Source
Implemented AWS Bedrock integration for LLM tool calling, enabling function-based agentic workflows in the Haystack 2 open source framework.
Built a prototype logistics management system using Supabase and Flutter, showcasing real-time tracking and project visualization capabilities.
Developperure and implementation of RAG (retrieval augmented generation) solutions in AWS for company HR agent.
Personal video game servers deployment, management and backup automation with AWS.