Data & AI Architect | Cloud-Native Solutions Engineer | Applied GenAI Developer

I design and build enterprise-grade data and AI platforms that combine the rigor of data architecture with the creativity of modern generative AI. My work bridges traditional analytics, MLOps, and emerging AI frameworks — always with an emphasis on governance, trust, and explainability.

• Cloud Platforms: AWS (Redshift, Glue, S3, Lake Formation, SageMaker, Bedrock), GCP (BigQuery, Vertex AI)
• Data Architecture: Lakehouse, Data Mesh, Governance & Lineage, ETL/ELT pipelines
• AI/ML: LLM integration, Retrieval-Augmented Generation (RAG), LangChain, Vector Search (FAISS/Chroma)
• Engineering Stack: FastAPI, Python, Neo4j, PostgreSQL, Docker, React
• Dev Tools: AWS CodeWhisperer, GitHub Copilot, Amazon Q

Exploring reinforcement learning and simulation environments to model real-world decision-making and adaptive AI behavior in competitive racing contexts. Built as a testbed for autonomous agent training and reward-optimization strategies.

A modular RAG + Agentic AI framework supporting local and hybrid LLMs (Mixtral, LLaMA 3, GPT-4o).
Implements vector search (FAISS), semantic tagging, FastAPI endpoints, and multi-agent orchestration for document Q&A, reasoning, and secure enterprise AI workflows.

Visit Fox River AI — my applied AI consulting and product studio focused on delivering secure, explainable, and high-performance AI systems for small to mid-sized businesses.

Always building the bridge between knowledge, reasoning, and intelligent automation.