Hadi Amiri

Applied AI / GenAI Engineer at Revolution Data Platforms

Built production RAG ingestion and retrieval pipelines for enterprise clients, including hybrid dense+sparse retrieval with Qdrant, vision-LLM enrichment, chunking, cross-encoder reranking, and content-hash deduplication. Implemented RAG fallback strategies leveraging Cosmos DB. Developed agentic systems using LangGraph state machines for multi-skill tool orchestration, provider-agnostic LLM clients (Anthropic, Azure OpenAI, Azure AI Foundry), MCP tool integration, and human-in-the-loop gating. Created LLM evaluation harnesses with synthetic golden datasets using RAGAS and DeepEval, and added observability via Langfuse (datasets, tracing, AgentOps) on production Kubernetes. Delivered cloud data engineering capabilities including SSIS-to-Fabric/Databricks migration automation, medallion (bronze/silver/gold) architecture, Unity Catalog and Delta Live Tables, data masking, and event-driven schema-change detection. Deployed and governed AI services on Azure ML managed endpoints with Docker

Network IT Assistant at Bell Technical Solutions

Diagnosed and resolved telecommunications and network system issues, supporting configuration, maintenance, and upgrades for enterprise environments.

Research Assistant / Teaching Assistant at University of Ottawa

Conducted research on approximate Bayesian neural networks for inference-time uncertainty quantification in probabilistic classification, improving reliability of clinical decision-making. Built a multimodal emotion and bipolar-severity assessment system using VGG-Face and FER2013 for visual features, a deep belief network for audio, early fusion, and an LSTM for video classification on datasets exceeding 2M frames. Supported teaching as a TA for courses including uncertainty evaluation in machine learning, computer architecture, and electrical circuits.