Godwin Olagunju

Godwin Olagunju

AI Engineer

Lagos, NG.

Projects

Retail Store E-Commerce Deployment: Kubernetes-based Microservices Architecture

Engineered a scalable microservices architecture on AWS EKS, utilizing Terraform for Infrastructure as Code to automate full-stack provisioning and cluster management. Designed a secure network topology within AWS VPC by implementing public and private subnets alongside Elastic Load Balancing to optimize traffic distribution for High Availability. Further secured the infrastructure by integrating Amazon RDS for managed persistence, establishing strict access control policies to isolate and protect internal data traffic.

Lumora – AI Tax Compliance Assistant

The Challenge: Navigating Nigeria's tax policies is notoriously difficult for entrepreneurs. The complexity of the regulations often leads to unintentional non-compliance, resulting in severe fines or business shutdowns. There was a need for an accessible tool that could translate legal jargon into actionable business advice. The Solution: I built Lumora, a specialized AI web agent. Unlike generic chatbots, Lumora is built on a RAG (Retrieval-Augmented Generation) architecture. I utilized LangChain to orchestrate the application logic and Pinecone to index vast amounts of official tax data from the CAC. When a user asks a question, the system retrieves the specific legal clauses relevant to the query and passes them to the OpenAI model to generate an accurate, citation-backed answer. This bridges the gap between complex policy and business application.

EduPeerHub Cloud Infrastructure

The Challenge: EduPeerHub required a robust, accessible platform to help students from under-resourced backgrounds prepare for exams. The infrastructure needed to be cost-effective yet capable of handling fluctuating traffic without downtime. The Solution: I led the end-to-end deployment of the platform on AWS. My primary focus was automation and performance. I established a secure CI/CD pipeline to bridge the frontend and backend, ensuring that updates could be pushed instantly without disrupting users. To handle traffic spikes, I configured Nginx as a high-performance proxy, which optimized resource usage and request handling. I also secured the platform with end-to-end SSL encryption to protect user data.

Public Web Server Deployment

The project demonstrates how to build a production-ready CI/CD pipeline that automatically deploys a static website to a cloud Virtual Machine running Ubuntu and NGINX. By leveraging GitHub Actions, the workflow replaces manual file transfers with a secure automation sequence: whenever code is pushed to the repository, the system authenticates via SSH keys, uploads the latest assets to the server, and safely reloads NGINX to reflect changes instantly. This setup provides a "bare metal" alternative to managed platforms like Vercel, giving you full control over your infrastructure while ensuring that your live site is always in sync with your code.

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Sitelytics

Played a pivotal role in the engineering team for Sitelytics by architecting the server-side foundation of the application. While partnering with mobile developers to define data models and API specifications, focused heavily on DevOps enablement—automating deployment workflows, provisioning cloud resources via Ansible, and implementing centralized logging to give the team visibility into system performance and AI scanning processes.

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Skills

Machine Learning

Python, scikit-learn, TensorFlow, PyTorch, Keras, Model Development, Algorithm Design

Data Science

Pandas, NumPy, Jupyter Notebook, Data Analysis, Statistical Modeling, Data Visualization

Backend Development

Python, Flask, FastAPI, SQL, NoSQL, Redis, RESTful APIs, Database Management

MLOps & DevOps

Docker, Kubernetes, CI/CD (GitHub Actions), MLflow, Infrastructure as Code, Configuration Management, Monitoring & Logging

Cloud Platforms & Serverless

AWS, Azure, GCP, Terraform, Serverless Architectures, Cloud Deployment

Agentic Workflows

LangChain, Langgraph, Vector Databases, Prompt Engineering, LLM Integration

Communication

Active Listening, Presentation Skills, Interpersonal Communication

Problem Solving

Analytical Thinking, Root Cause Analysis, Strategic Solutions

Teamwork & Collaboration

Cross-functional Collaboration, Team Leadership, Conflict Resolution

Adaptability

Agile Methodologies, Change Management, Continuous Learning

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Work

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Peepalytics

AI Engineer

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HNG

Software Engineer

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Skoutwatch

AI Engineer

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HNG

DevOps Engineer

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Education

Cloud Engineering

AltSchool Africa

Mechanical Engineering

Federal University of Technology, Minna

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Certificates

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HNG DevOps Finalist

Hotelsng

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Introducing Generative AI with AWS

Udacity

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Diploma In Cloud Engineering

AltSchool Africa

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Kubernetes and Cloud Native Associate (KCNA)

The Linux Foundation

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Certificate of Proficiency

HNG INTERNSHIP

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Microsoft Certified: Azure AI Fundamentals

Microsoft

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Deep Learning Specialization

Coursera

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Languages

English

Yoruba

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About

Hey, I’m Godwin Olagunju — a machine learning engineer with a solid background in backend development. I like building systems that make data come alive — from training ML models to deploying them as APIs that people can actually use.<br><br>I’ve worked on projects that blend AI with everyday problems, like Lumora, a chatbot that helps business owners understand taxes and regulations without all the confusion. I enjoy the challenge of building tools that feel simple on the surface but run on smart, well-structured systems underneath.<br><br>Most of my work sits at the intersection of machine learning, backend engineering, and product thinking. I spend a lot of time in Python, FastAPI, PyTorch, and SQL, and I care about writing code that’s both clean and scalable.<br><br>Outside of tech, I’m fascinated by cryptocurrency and how digital finance is reshaping economies. I also keep a casual eye on the stock market — not just for the numbers, but for the stories behind how markets move.<br><br>At the core of it, I like learning how systems — human or machine — make decisions, and how we can make them a little smarter.

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