Verified Member

I design and deploy AI-driven systems that solve ambiguous, high-stakes business problems—owning work from architecture through production. My core expertise is multi-agent architectures, LLM-powered automation, and distributed platforms that scale under pressure. I specialize in turning vague requirements into resilient, measurable systems and evolving them using real production signals. At GoTeam, I lead the design and rollout of a multi-agent AI automation platform across research, analysis, and project management. I built n8n-based orchestration with intelligent task routing, drove model selection that achieved 40% cost savings with o4-mini for routine research, reduced research time by 80%, and created comment-triggered NLP systems saving 15+ hours weekly at 95% accuracy. Previously at Tolstoy, I led architecture for a multi-agent AI communication system serving 10,000+ businesses. I introduced a weighted parallel execution model with confidence-based ranking, increasing response accuracy by 65% while cutting reply time by 75%. I also re-architected serverless infrastructure to scale traffic 3× while reducing costs by 20%. At Bilis Delivery, I owned end-to-end design of a microservices platform processing 10,000+ orders with 99.9% uptime. I implemented zone-based driver matching that cut wait times by 80%, real-time WebSocket tracking that reduced Maps API usage by 60%, and a modular Laravel architecture that improved maintainability by 60%. I’ve also shipped university platforms that reduced queue times by 80% and built LangGraph-based multi-agent chat systems that autonomously resolve 85% of student queries using specialized agent pipelines and retrieval strategies. Currently focused on building serverless AI platforms, establishing high-leverage engineering patterns, mentoring teams in systems thinking, and delivering measurable ROI through iterative, risk-aware deployment.