TJ.ADEBAYO
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Kickoff — Player Profile

Oluwatojuba "TJ" Adebayo

Computer Science graduate building LLM-powered applications, RAG pipelines and production-grade AI systems — from retrieval architecture through to deployment. Comfortable across the full stack with Python, React and Node.js, and just as happy debugging a CI pipeline as designing a prompt.

POSITIONSoftware Engineer — AI/LLM Systems
BASED INEdinburgh, UK
CONTACTtjadebayo04@gmail.com

AI & LLM

Anthropic APIOpenAI APIPrompt Engineering RAG Multi-agent Architecture

Languages & Web

PythonJavaScriptTypeScript ReactNode.jsFastAPI FlaskSQLJava

Data, ML & Cloud

SupabaseFirebase scikit-learnNumPyOpenCV DockerCI/CD

Match Experience

Full Stack Developer — Intellidigest

Edinburgh, UK · June 2024 – July 2024

  • Designed and shipped production features for a live platform, including account management and analytics, owning the full lifecycle from solution design through to deployment.
  • Translated business requirements into working software, reducing post-deployment errors from 20% to 4% through rigorous testing, debugging and CI/CD practices.
  • Integrated REST APIs and third-party services into the backend, implementing cloud-based NoSQL storage with Firebase.
  • Used Git with structured branching strategies for version control and cross-functional collaboration.
  • Led development demos and feedback cycles, communicating technical progress clearly to stakeholders.
ReactJavaScriptPython JavaFirebaseREST APIs

Training Ground

BSc (Hons) Computer Science — Software Engineering

Heriot-Watt University, Edinburgh · Sept 2021 – June 2025 · 2:1

  • Strong foundation in software architecture, system design, data structures, algorithms and object-oriented programming.
  • Practical experience across the full SDLC using Agile and DevOps methodologies, with automated testing, CI/CD and version control.
  • Third-year project: built a real-time collaborative whiteboard with React.js and Socket.io, using an event-driven architecture with live state sync across concurrent users.
Software ArchitectureAgileDevOps Socket.io

Highlight Reel

Football Match Outcome Predictor

An ML pipeline predicting win / draw / loss from historical match data — team form, goals scored and conceded, home/away splits. Compared Random Forest against Logistic Regression using cross-validation, confusion matrices and F1 score to pick the strongest model.

Pythonscikit-learnPandasMatplotlib
View on GitHub →

THERMAL — Drone Heat Loss Detection

A production-grade pipeline processing thermal drone footage to detect building heat loss and generate retrofit reports, cutting manual survey time from 3 hours to under 1 minute per property. Shown at the Anthropic AI Expo, Edinburgh. Built an LLM-powered orchestration layer over the Anthropic Vision API and a RAG-adjacent retrieval pipeline for physics-based estimates with 95% confidence intervals.

PythonOpenCVNumPySciPyVision API
View on GitHub →

News Recommendation Platform

A full-stack AI application with a modular REST API backend applying NLP and LLM-powered recommendations, with a document ingestion and retrieval pipeline analogous to RAG. User preferences stored in Firebase, with the model continuously re-ranking content from live interaction signals.

PythonFlaskReactFirebaseLLM APIs
View on GitHub →

Full Time — Get In Touch

Let's build something.

Open to software engineering and AI/LLM roles. Reach out below.

tjadebayo04@gmail.com linkedin.com/in/olu-adebayo04 github.com/tadebayo04

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TJ ADEBAYO

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