Marven Ayong Acojedo

Led the design and deployment of large language model applications — including generative AI, NLP, and multimodal RAG pipelines — helping clients innovate faster and work more efficiently. Built and scale cloud-native AI systems on AWS, combining NLP and computer vision to solve enterprise challenges. Designed advanced agentic architectures that automate complex workflows and enhance decision-making. Developed new prompt engineering methods and improved semantic search by integrating vector databases for higher retrieval accuracy. Ensured seamless web integration by connecting AI systems with React front-ends, FastAPI back-ends, and RESTful APIs. Mentored engineers and collaborated closely with business teams to ensure LLM solutions align with TechVision’s strategy and mission.

Led design and deployment of LLM applications, generative AI, NLP, and multimodal RAG pipelines; built cloud-native AI systems on AWS; designed agentic architectures; implemented prompt engineering and enhanced retrieval with vector databases; integrated AI with React front-ends, FastAPI back-ends, and RESTful APIs; mentored engineers and aligned solutions with business strategy.

Designed and implemented advanced NLP pipelines using transformer models and LSTMs, enabling Fortune 500 clients in healthcare, legal, and technology to achieve domain-optimized performance. Managed LLM fine-tuning and adaptation pipelines, resulting in over 40% improvement in accuracy, efficiency, and system reliability in operational deployments. Architected and deployed secure, scalable NLP & LLM systems on AWS, GCP, and Azure, ensuring enterprise readiness and compliance. Enhanced user-facing applications by applying advanced prompt engineering and context optimization, resulting in greater responsiveness and improved user satisfaction. Built statistical models, LSTM-driven sequence frameworks, and supervised learning pipelines that served as the backbone for enterprise-wide AI scalability.