I help engineers, founders, and teams build real-world AI systems that actually work in production - not just demos. Right now, I’m working on agentic AI systems, observability, and evaluation frameworks at scale, including LLM-based platforms handling complex workflows, tracing, and reliability challenges. If you’re: Trying to build or scale AI agents / RAG systems Struggling with LLM reliability, hallucinations, or evals Confused about how to productionize AI (not just prototype) Designing data pipelines for AI workloads Exploring AI architecture decisions (what to build vs what to avoid) I can help you cut through the noise and get clarity fast. What you’ll get from a session: Clear architecture direction (no fluff) Honest feedback on your approach (I won’t sugarcoat) Practical, production-ready suggestions Insights from real systems handling scale Background: Senior Software Engineer (AI Systems) @ RBC Borealis AI (working on large-scale AI + data platforms) Built RAG systems, real-time pipelines, and LLM-based automation systems Experience across Data Engineering + ML + Applied AI 🎓 Dalhousie University (MACS) 🏆 National Olympiad Winner If you’re serious about building something meaningful in AI - happy to help.