
Engineering Philosophy & Credentials
From computational fluid mechanics and mechanical engineering to autonomous reinforcement learning agents, multi-agent capability protocols, and spatial computing hardware.
The Journey: Analytical Rigour to Autonomous Intelligence
I started in mechanical engineering, earning a First-Class Honours degree with an emphasis on mathematical modeling, thermodynamics, and fluid mechanics. Engineering taught me the fundamentals of physical constraints, systematic diagnostics, and numerical optimization—principles that directly shaped my transition into high-performance software engineering and machine learning.
At V-Nova, I operated at the intersection of video compression codecs, GPU pipelines, and distributed cloud computing. Collaborating with Meta and NVIDIA engineers, I designed automated testing harnesses that reduced distributed experimentation cycles from three hours to seconds and enabled scalable VMAF/PSNR benchmarks across thousands of video streams.
At Roku, my focus evolved to the cutting edge of AI-assisted software delivery: building Roku Explorer (an autonomous exploratory QA platform using reinforcement learning, multimodal vision, and ChromaDB RAG to explore device UIs), QANTUM (a Slack-native multi-agent orchestrator connecting specialized agents via capability protocols), and Forge (an AI agent authoring regression test suites in isolated git worktrees). This work represents a patent-pending innovation (US/EU) for autonomous software verification.
Outside my day role, I am the solo founder and architect of Augma, building a minimalist headband-monocle augmented reality wearable combining edge YOLO26 computer vision, MediaPipe wrist-gesture interaction, and an ergonomic counterbalance architecture designed to replace bulky smart glasses.
Patent pending and a published NVIDIA article
Autonomous software verification
The Roku stack — Explorer, QANTUM, and Forge — is a patent-pending invention for turning manual QA into a data-driven process that finds functional and visual defects on devices with less manual oversight.
Read it on the career timelineEnabling Customizable GPU-Accelerated Video Transcoding Pipelines
Written with NVIDIA engineers at V-Nova. The article covers VC6 codec performance and a GPU-accelerated transcoding pipeline, published on NVIDIA’s developer blog.
Read the NVIDIA articleEducation & Honours
Bachelor's Degree in Mechanical Engineering (BEng Hons)
Coventry University
- Graduated with First-Class Honours, demonstrating rigorous analytical and computational aptitude.
- Achieved a perfect score (100%) in the advanced Fluids & Heat Transfer engineering module.
- Formed strong foundation in numerical methods, fluid mechanics, CAD simulation, thermodynamics, and algorithmic problem solving before transitioning into software and machine learning.
- Studio projects — prosthetic arm, Kitau self-balancing tray, FEA mass/vibration optimisation, heat-exchanger CFD, and autonomous-car control — are restored on theengineering archive.
Verified Industry Certifications
AWS Certified Solutions Architect – Associate (SAA)
COREAmazon Web Services
CloudAWS Certified Machine Learning – Specialty (MLS)
COREAmazon Web Services
CloudTensorFlow Developer Certificate
COREGoogle Developers Certification
Machine LearningISTQB Certified Tester Foundation Level (CTFL)
COREISTQB / BCS
Software Engineering & TestingIBM Data Science Professional Certificate
COREIBM
Machine LearningDeep Learning Specialization
DeepLearning.AI (Andrew Ng)
Machine LearningMachine Learning Specialization
Stanford Online
Machine LearningMachine Learning DevOps Engineer
Udacity Nanodegree
Machine LearningBuilding Systems with ChatGPT API & Agentic Workflows
DeepLearning.AI
Machine LearningLinux Specialisation & Kernel Architecture
Coursera / Linux Foundation
Systems & LinuxSoftware Architecture & Design of Modern Large-Scale Systems
Udemy Advanced Engineering
Software Engineering & TestingCUDA Basics & High Performance GPU Computing
Udemy / Parallel Computing
Systems & LinuxTechnical Skills by Domain
Core AI & Agent Systems
- Reinforcement Learning (PPO/LSTM)
- Multi-Agent Orchestration
- Model Context Protocol (MCP)
- RAG & Vector Databases (ChromaDB, Qdrant)
- Vision-Language Models (VLMs)
- LiteLLM / Claude Agent SDK
- YOLO26 & MediaPipe Computer Vision
Languages & Core Stack
- Python (Advanced)
- TypeScript / JavaScript
- C++
- SQL (PostgreSQL, MySQL)
- Bash / Shell Scripting
- MATLAB & R
Cloud & Distributed Infrastructure
- AWS (EC2, S3, RDS, Lambda, VPC)
- Terraform (IaC)
- Docker & Container Orchestration
- Kubernetes (K8s)
- GitLab CI / GitHub Actions / Jenkins
- Distributed Video Computing & Transcoding
Frameworks, APIs & Testing
- FastAPI & Flask
- Pytest & Automated Test Suites
- Selenium & Cucumber BDD
- React & Astro
- Alembic Database Migrations
- Slack Bolt API & Jira REST API
Want to discuss engineering or advisory?
Direct comms, LinkedIn connections, and repository code reviews are welcome.