Work

Selected projects.

Systems built to spec, documented in full. Each project is an exercise in architecture decisions, not just implementation.

Screenshots / node graphs
drop here
Intensity:
P-01
Audio Systems Game Dev Unreal Engine 5

SlamPunk — Dynamic Mix Engine

Lead Audio Systems Designer & Music Producer

A logic-driven dynamic audio engine for SlamPunk — a competitive future-sport game blending tag and basketball. Engineered a 15-stem interactive music system that mirrors player performance in real time, escalating from a minimal atmospheric floor to a dense triumphant climax while maintaining surgical clarity for competitive gameplay cues.

Timeline
14 weeks / ~600hrs
Grade
100% — Grade A
Architecture
15-stem / 3 intensity layers
BPM Grid
140 BPM locked
Unreal Engine 5 MetaSounds Blueprints FL Studio 24 REAPER v7 Vital (Wavetable)
15-stem dynamic music system split across 3 match intensities and 5 discrete instrument busses
Real-time sidechain ducking — music stems duck dynamically when parkour SFX or commentator lines trigger
Hierarchical submix tree with spectral carving — Data Bus hard high-passed at 200Hz to preserve low-end headroom
Global Music Manager Blueprint locks all transitions to 140 BPM grid — zero rhythmic stutter on intensity escalation
Fully modular pipeline — new arenas and themes hot-swap into established mix framework without breaking thresholds
Case Study GitHub
ATLAS boot sequence — SPECULAR-CORE initialising WSL2 and Docker ATLAS node active — Ubuntu subsystem online, Docker engine ready
Open WebUI screenshot — drop here
P-02
AI / Local LLMs RAG DevOps

Ramone — Local AI System

Architect & Systems Engineer

A fully self-hosted private AI infrastructure — zero cloud dependency, zero data egress. Five LLMs served via Ollama on local hardware, wrapped in Docker, accessed through Open WebUI with ten specialised workbots backed by RAG knowledge bases. Everything lives on a dedicated NVMe drive: portable, rebuildable in under 30 minutes.

GPU
RTX 5070 — 12GB VRAM
RAM
64GB DDR5
Models
5 LLMs / 3b–32b params
Workbots
10 specialised agents
Ollama Docker WSL2 Ubuntu Open WebUI RAG Pipelines Windows Batch
Full data sovereignty — conversations, documents, and RAG knowledge bases never leave local hardware
Custom ATLAS_BOOTSTRAP.bat auto-starts full stack on boot — Docker, Ollama, Open WebUI with live health checks
RAG knowledge bases built from chunked university lecture PDFs — Academic Vector Index grounded in real course material
Hardware portable — entire system on L:\ NVMe, rebuildable on new hardware in under 30 minutes
Model selection matched to task profile: 3b for speed, 32b for deep reasoning and RAG retrieval
Case Study GitHub