thothbot

Precision medicine company focused on gene therapy discovery and development (geneease.com) • Architected and developed an AI agentic platform for biologists and scientists - enabling intelligent data mining, automated validation pipelines, and natural language interaction with complex research datasets • Designed multi-agent workflows using LangGraph, building AI agents with 20+ integrated bioinformatics tools and connections to online scientific databases • Integrated Nextflow engine into internal research processes, streamlining reproducible bioinformatics pipeline execution • Built unified Research Hub microservice architecture connecting AI-driven tools with manual research workflows, significantly improving research productivity for scientists • Lead technical hiring processes, developing evaluation frameworks and conducting interviews for engineering and computational biology positions

• Architected and delivered a bookkeeping automation app: end-to-end infrastructure design, Kubernetes deployment, Apple App Store publication • Designed Data Center in Vigo for AI/ML workloads: GPU cluster architecture, Docker & Kubernetes orchestration, GitLab CI/CD pipelines • Defined system architecture for a hybrid e-commerce platform and event-focused Push-to-Talk app, ensuring modular, scalable services • Led a team of 7 developers; drafted the next-gen ERP architecture integrating logistics, finance, CRM, and warehouse modules • Engineered AI-driven performance-tracking features across multiple tools, selecting technologies for long-term maintainability • Implemented observability stack with Prometheus, Grafana, and centralized logging for production monitoring and alerting • Acted as strategic technical advisor to executives, evaluating emerging technologies and driving future-proof software solutions

Real-Time Cryptocurrency Trading Platform • Engineered a low-latency, distributed order-management system in Java with Akka - supporting order creation, entry, risk monitoring, and real-time market-data processing • Built a scalable data-ingestion network that aggregates live trade and order feeds from multiple exchanges, storing time-series data in InfluxDB for high-throughput reads and writes • Designed and implemented order-handling interfaces, rule engines, and utility services to ensure sub-millisecond response times under heavy load • Optimized data pipelines with low-level performance tuning, enabling rapid back-testing and live trading scenarios • Developed distributed trading-algorithm simulators, leveraging cluster-computing patterns for parallel strategy evaluation • Led R&D on AI-driven market-movement forecasts, training neural-network models on historical and social-media data for predictive insights • Delivered end-to-end data visualization dashboards, empowering traders with real-time analytics and actionable metrics