Chibuzor Authur

I help businesses automate workflows, enhance customer experience, and drive measurable results through intelligent, LLM-powered solutions. As an AI/ML Engineer and Full-Stack Generative AI Developer, I specialize in building scalable systems that combine automation, reasoning, and data-driven intelligence.

I develop Agentic AI systems, Retrieval-Augmented Generation (RAG) architectures, and Conversational AI platforms that transform complex data into actionable insights using Python, LangChain, OpenAI API, and modern vector databases.

What I Build:

• RAG & Knowledge Systems – Built retrieval-augmented pipelines with FAISS and pgvector to boost context relevance and answer accuracy.

• Conversational AI & Chatbots – Delivered production assistants that reduced support workload by 45% and increased engagement by 35%.

• Automation & Multi-Agent Workflows – Designed proposal generators, email agents, and workflow automations that cut manual effort by 80%.

• Cloud & MLOps Deployment – Deployed scalable AI solutions on AWS, GCP, and Docker with secure API endpoints for seamless integration.

Tech Stack:

Python • LangChain • OpenAI API • LangGraph • Autogen • FAISS • pgvector • FastAPI • Next.js • Streamlit • PostgreSQL • Docker • CI/CD • NLP • Prompt Engineering • Multi-Agent Systems

Client Impact:

• Zenovo AI (U.S.) – Built proposal automation reducing drafting time by 80%.

• Junify AI (Australia) – Delivered conversational intelligence improving workflow efficiency by 60%.

• EmailGen – Created a multi-agent email system that cut outreach time by 70% and boosted campaign engagement by 35%.

I’m passionate about building AI systems that think, learn, and deliver measurable business impact. If you want to integrate RAG, agents, or automation into your business, I’ll help you deploy fast, reliable, and revenue-driven AI solutions.