Hussein Moukalled

• Drove AI engineering initiatives focused on advanced AI solutions and strategic project execution.
• Developed interactive AI avatars for interview preparation and networking, applying expertise in AI agents and
natural language processing.
• Delivered end-to-end AI solutions from research and conceptualization through implementation, testing, and
iterative refinement.
• Translated complex AI concepts into practical, user-facing applications with clear user value and impactful
real-world outcomes.
• Conducted continuous experimentation and refinement to optimize performance and user experience across
AI systems.

• Designed, built, and maintained full-stack features for a gamified, AI-powered language-learning platform,
owning work end-to-end from React.js interfaces through FastAPI backend services and AI integrations.
• Developed and maintained REST APIs and backend services powering AI-driven functionality, including
PostgreSQL data modeling, service integration, and application logic for language processing.
• Integrated AI and NLP components — conversational agents, personalized recommendations, and speech
services — into production systems supporting diverse spoken-language varieties.
• Built and optimized data pipelines and learner-personalization logic, leveraging LLM and RAG techniques to
deliver adaptive, culturally-aware learning content.
• Containerized services with Docker and contributed to CI/CD pipelines on AWS, ensuring reliability,
performance, and security of deployed systems.
• Collaborated with product, design, and AI teams to translate requirements into scalable solutions, contributing
to architecture decisions and the technical roadmap ahead of the product launch.

• Selected for a competitive working-student program, demonstrating strong technical aptitude and reliability.
• Managed office operations independently and resolved a wide range of technical issues, ensuring smooth dayto-day operations; recognized for impactful performance.

• Worked as an AI/ML research engineer in collaboration with AUB and AUBMC, contributing to a $100, 000
grant application.
• Designed and led the technical development of a predictive model for immunotherapy toxicity in patients,
from concept to validation.
• Collaborated closely with multidisciplinary teams (engineers, doctors, nurses) to translate clinical
requirements into scalable AI solutions.
• Operated in a complex, research-driven environment, applying LLM and RAG principles to data interpretation
and model development.

• Applied expertise as a researcher, AI engineer, and consultant for innovative startups.
• Designed and architected a full system for real-time sign-language translation into spoken dialect, selecting
optimal components and technologies.
• Led end-to-end development — research, system design, implementation, testing, and iteration — with a
focus on AI agents for real-time processing, prioritizing performance, accuracy, and usability in production.