Alexander B.

I help turn complex ideas into reliable software — particularly AI-powered applications, automation platforms, and quantitative trading systems. I'm a software engineer with a background in applied mathematics and scientific research. My work combines hands-on Python development with system architecture and technical leadership, from clarifying the problem and testing an approach to implementation and production integration. AI systems and automation I build AI-powered workflows, assistants, and research tools, including LLM integrations, multi-agent orchestration, and persistent memory. My focus is on the engineering that makes these systems useful beyond a demo: clear execution boundaries, validation, recovery, monitoring, and human approval where it matters. I use AI-assisted development where it adds value, without treating generated code as a substitute for engineering judgment or verification. Quantitative and trading software I build the infrastructure that connects quantitative research with live execution: market-data pipelines, backtesting frameworks, strategy implementation, broker and exchange integrations, and monitoring dashboards. My focus is mid-frequency algorithmic trading, with particular attention to reproducible research, realistic execution assumptions, and consistency between backtesting and live behavior. My experience spans stocks, futures, Forex, crypto, and prediction markets. One platform I helped build from scratch supported eight production trading bots and $1.5M in trading capital. Professional poker software I develop specialized private applications for professional poker players, combining mathematical modeling, data analysis, and software engineering. These projects are confidential, so I discuss relevant experience without disclosing proprietary methods or implementation details. Scientific background and working approach I hold an MSc in Applied Mathematics from MEPhI and previously spent five years leading a research laboratory. That background still shapes how I work: formulate the problem carefully, question assumptions, evaluate evidence, and build a solution that fits the actual task. My technical foundation is Python, with tools such as NumPy, pandas, SciPy, scikit-learn, Django, PostgreSQL, and Docker. I also bring experience in real-time data processing, image processing, APIs, and custom integrations. I'm interested in long-term collaborations where I can contribute both as a hands-on engineer and as a technical lead. I value clear communication, meaningful ownership, and understanding the domain and the people who will use the software. If you need someone who can engage with both the mathematics and the engineering — and help clarify the problem before building the solution — we'll likely work well together.