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Solomon Enamudu

@solomonenamudu

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AI/ML Engineer building Aloko, an integrated AI platform with end-to-end workflows, assessment, and automated marking.

Nigeria

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I’m the founder and builder of Aloko, an integrated AI platform spanning business, university, and creator workflows. I developed its end-to-end AI features across frontend, backend, data, and model integrations.

For Aloko, I built FastAPI services and React/Vite interfaces backed by PostgreSQL. I also implemented authentication, authorization, ownership checks, and organizational data isolation.

In Aloko University AI, I developed workflows for courses, students, assessments, submissions, and AI-assisted marking. Lecturers review and approve results before they’re finalized.

I built a RAG-based flood information assistant that processes and chunks documents, creates SentenceTransformers embeddings, and retrieves evidence with FAISS for grounded LLM responses. I also developed a heart disease prediction application and a Telegram AI coach bot.

Experience

Work history, roles, and key accomplishments

AI Engineer / Full-Stack Developer

Aloko University AI

Built role-based workflows for university administrators, faculty administrators, HODs, lecturers, and students. Designed university-level data isolation and independent lecturer workspaces.

Python fastAPI React PostgreSQL REST APIs AI Assisted Workflows Role based Access Data Isolation AI Marking Webhooks Logging

Founder / AI Engineer / Full-Stack Developer

Aloko

Architected and developed end-to-end AI workflows across frontend, backend, data, and model-integration layers. Built FastAPI services and React/Vite interfaces backed by PostgreSQL.

Python fastAPI React Vite PostgreSQL REST APIs AI LLM Integration Authentication Authorization Data Isolation AI Assessment Automated Marking Debugging Deployment

Machine Learning Engineer

Heart Disease Machine Learning Application

Prepared and processed the dataset, trained classification models, and evaluated model performance. Connected the trained model to an interactive Streamlit prediction workflow.

Python Machine Learning Streamlit Data Preparation Model Training Model Evaluation

AI/ML Engineer

Flood AI Assistant

Built the document-to-answer RAG pipeline: processing, chunking, embeddings, vector retrieval, context, and LLM response. Generated semantic embeddings with SentenceTransformers and implemented vector retrieval with FAISS.