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Engineering

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Production-grade applications built for scale. Real-time systems, multiplayer games, and backend optimizations with measurable impact.

Real-time Gaming

WebSocket, WebRTC, Game State

Web Applications

Full-stack, APIs, Databases

Performance

Optimization, Caching, Async

#01

Portal Gambit

Real-time Chess Variant with Recursive Logic

A complex chess variant featuring portal mechanics that allow pieces to teleport across the board. The engine handles recursive move validation to prevent infinite loops during portal traversal, synchronized in real-time via Firebase.

Features

  • Recursive move validation algorithm for portal traversal
  • Optimistic UI updates with Firebase transactions
  • P2P Voice Chat using WebRTC (PeerJS) signaling
  • Automated ELO calculation via Cloud Functions

Metrics

Test Coverage15+ Suites
Latency<100ms
Voice QualityP2P HD

Tech Stack

ReactFrontend
FirebaseReal-time DB
FastAPIBackend
PeerJSWebRTC
DockerDevOps
portal-gambit.js
1// CustomChessEngine.js: Handling "Simultaneous Existence"
2moves({ square, verbose, visited } = {}) {
3 // Prevent infinite recursion in portal loops
4 if (!visited) visited = { portals: new Set(), simulChecked: new Set() };
5
6 const isOnPortal = this.portals[square] !== undefined;
7 if (isOnPortal && !visited.simulChecked.has(square)) {
8 visited.hasTraversedPortal = true;
9 const linkedSquare = this.portals[square].linkedTo;
10
11 // Virtual move: Place piece at exit to calculate potential captures
12 const tempPiece = { ...this.get(square) };
13 this.put(tempPiece, linkedSquare);
14
15 // Recursive call from the new perspective
16 const linkedMoves = super.moves({ square: linkedSquare, verbose: true });
17 // ... merge moves and restore board state ...
18 }
19}
#02

TerraQuest

High-Concurrency Geo-Gaming Platform

A competitive geography game built with Go. Features a high-performance worker pool for ingesting and validating 81,000+ global locations concurrently, ensuring a massive dataset for multiplayer lobbies.

Features

  • Concurrent data ingestion using Go Worker Pools
  • Atomic counters for thread-safe statistics
  • WebSocket lobbies with mutex-locked state management
  • Geodesic distance calculation for scoring

Metrics

Locations81,000+
ConcurrencyWorker Pool
Lobby Size8 Players

Tech Stack

Go (Gin)Backend
Vue 3Frontend
PostgreSQLDatabase
Gorilla WSReal-time
GORMORM
terraquest.go
1// populate_locations.go: Worker Pool Pattern
2for i := 0; i < *workerCount; i++ {
3 workerWg.Add(1)
4 go func(workerID int) {
5 defer workerWg.Done()
6 for candidate := range jobs {
7 atomic.AddInt32(&totalProcessed, 1)
8 // Validate via Google Street View API
9 if dbErr := workerBatch.Add(newLocation); dbErr != nil {
10 atomic.AddInt32(&totalErrors, 1)
11 } else {
12 atomic.AddInt32(&totalValidated, 1)
13 }
14 }
15 }(i)
16}
17// Feed jobs to buffered channel
18for i := 0; i < numToProcess; i++ { jobs <- allCandidates[i] }
#03

GRIG Technologies

Backend Optimization & Microservices

Optimized certificate generation pipeline by implementing asynchronous processing. Migrated legacy endpoints to a scalable microservice architecture using Flask and Firebase, resulting in a 98.3% reduction in processing time.

Features

  • Async processing for PDF generation tasks
  • Microservice architecture for alerts (FastAPI)
  • Supabase object storage evaluation and prototype
  • CI/CD pipelines with GitHub Actions

Metrics

Time Reduction98.3%
Data Efficiency+40%
APIs Built10+

Tech Stack

PythonBackend
FlaskAPI
FirebaseDatabase
KubernetesOrchestration
SupabaseStorage
grig-technologies.py
1# Flask-RESTx API Structure (Architectural Sample)
2@api.route('/certificates/generate')
3class CertificateGeneration(Resource):
4 @api.expect(cert_model)
5 def post(self):
6 """Async generation trigger"""
7 data = request.json
8 # Offload heavy PDF rendering to worker queue
9 task_id = async_worker.enqueue(
10 render_certificate,
11 user_id=data['uid'],
12 template=data['template']
13 )
14 return {'task_id': task_id, 'status': 'processing'}, 202