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Schedule Interview NowBeing part of Softaims has allowed me to see the full spectrum of what technology can achieve when guided by empathy, discipline, and creativity. Each assignment, regardless of size, represents an opportunity to bring clarity to complexity and to turn ambitious ideas into tangible outcomes. I’ve come to realize that successful development isn’t just about writing code—it’s about listening carefully, understanding deeply, and designing thoughtfully. Every client brings unique challenges, and I make it a priority to align my work with their goals, ensuring that the end result is both effective and lasting. Softaims fosters an environment where collaboration is not optional—it’s essential. The collective expertise within the team pushes me to think beyond conventional boundaries, to question, refine, and innovate. I believe that this process of shared learning and experimentation is what makes our solutions resilient and impactful. My ultimate goal is to build technology that feels effortless to use yet powerful in function. I approach every task with the mindset that small details can make a big difference. Through continuous refinement and dedication, I aim to contribute to the kind of work that not only serves today’s needs but anticipates tomorrow’s possibilities.
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I am the developer of tinyllm, a lightweight framework for developing, debugging and monitoring LLM and Agent powered applications at scale. The main goal of the library is to keep code as simple and readable as possible while allowing user to create complex agents or LLM workflows in production.
I am the founder of Rumorz, a platform for AI agents in financial markets. The application offers AI data infrastructure and tools to build custom agents for task automation and reporting for Traders, Investors and Financial Institutions. Website: https://rumorz.io Python SDK: https://github.com/rumorz-ai/rumorz
Client project: - Systematic trading strategy on Uniswap - Event-based framework in Python and C - Tick-level data - Same code for backtesting and production Outcome: - 99% accuracy in Backtest vs Live
This project is a demo for a tool to leverage AI to automatically - Read PDF documents - Parse specific fields - Map and input fields into a CRM (Salesforce) This automates 90% of the time spent reading and inputing docs into the CRM. This project leverages Python and tinyllm to document and AI processing. https://vimeo.com/918487779/026d6702ca
I have built the complete technology infrastructure for Lendmarq, a private real estate loan provider based in Miami, US. This included: - Managing 4 developers full-time - Building and maintaining a Salesforce CRM with API integrations - Website development and integration with CRM - Managing 60 internal users: training, documentation, daily communication - Bespoke Python automation scripts for daily tasks Website: https://lendmarq.com
Bachelor's degree in Financial markets and Statistics
2011-01-01-2015-01-01
Master's degree in Mathematics and Data Science
2018-01-01-2019-01-01