I design AI assistants that feel sharp, useful, and ready for real work.

• Design and deliver enterprise-grade AI systems, from architecture to production.
• Develop agentic workflows leveraging LLMs and external integrations.
• Own full lifecycle implementations across multiple client engagements.
• Translate ambiguous business problems into scalable technical solutions.
• Create reusable AI patterns for deployment, evaluation, and iteration.
• Advise strategically on AI adoption and system design.

• Developed custom LLMs with Python and Hugging Face, improving automation by 30%.
• Integrated LLM systems with internal data sources and APIs to enable context-aware, real-time decisioning across enterprise workflows.
• Defined evaluation frameworks and feedback loops to continuously improve model performance, driving measurable gains in accuracy and user experience.
• Optimized speech recognition with Google Cloud STT, reducing errors by 25%.
• Refined chatbot and LLM responses using CSAT and NLU metrics, raising CSAT by 15%.

• Developed IVAs and chatbots with Dialogflow CX and Python, increasing automation by 40%.
• Designed conversation flows and system logic to handle complex edge cases, improving containment rates and reducing human escalation.
• Delivered end-to-end implementations across multiple clients, managing deployment, testing, and iteration to ensure reliable production performance.
• Integrated APIs with Node.js and Express, reducing integration time by 40%.
• Implemented AI speech-to-text with Google Cloud and Twilio, cutting Tier-1 response time by 35%.

Formal computer science training that grounded my engineering fundamentals and supports the technical depth behind my current AI systems work.