I am a software engineer focused on building AI-driven decision systems that combine structured domain logic with machine learning. My work centers on designing scalable backends, data validation pipelines, and recommendation engines using Python, Node.js, and modern ML frameworks.
I have experience translating complex real-world variables into reliable software systems, working closely with domain experts to ensure models and rules are both technically sound and practically usable. This includes preprocessing heterogeneous datasets, defining clear data contracts, and architecting systems that can evolve as new data sources are introduced.
I am particularly interested in applied AI projects where correctness, explainability, and long-term maintainability matter more than experimentation alone. I am comfortable working in early-stage builds, making architectural decisions, and iterating quickly while maintaining engineering discipline.
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