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samuelbrhane/README.md

Hi πŸ‘‹, I'm Samuel Brhane

Senior Software & Machine Learning Engineer

I build intelligent, scalable, cloud-native systems
combining backend engineering, machine learning, and DevOps.

🌐 Website Β· πŸ’Ό LinkedIn Β· βœ‰οΈ Email


Production Platforms


πŸ” TokVigil

Application-Level AI Governance Β· SDK + VS Code Extension

πŸ”— GitHub: https://github.com/samuelbrhane/TokVigil
🌐 Website: https://tokvigil.com

A developer-first AI usage control platform that enforces limits, budgets, and governance policies directly inside application code rather than at the infrastructure or proxy layer.

Key capabilities

  • Python and TypeScript SDKs wrapping LLM calls
  • Per-user, per-feature, and per-plan usage enforcement
  • Per-request cost caps and token limits
  • Redis-backed real-time counters
  • Deterministic reason codes for blocked requests
  • Centralized audit logs and API key tracking
  • Environment isolation (dev / staging / prod)
  • BYOK support with consistent tracking
  • VS Code extension for in-editor usage visibility and policy inspection

Tech stack


πŸ“ˆ Nordict

Market Forecasting Platform Β· Multi-Horizon Probabilistic Modeling

πŸ”— GitHub: https://github.com/samuelbrhane/Nordict
🌐 Website: https://nordict.net

A production-grade market forecasting platform delivering multi-horizon probabilistic predictions (24H, 30D, 12W, 12M) with confidence scoring, alerts, and historical forecast-vs-actual analysis.

Key capabilities

  • Rolling inference pipelines with hourly and daily refresh cycles
  • Multi-horizon probabilistic forecasting with uncertainty estimation
  • XGBoost-based modeling with structured evaluation workflows
  • Authenticated dashboards for forecasts, alerts, and performance tracking
  • Forecast vs actual historical analysis
  • Subscription billing with plan-based feature enforcement
  • Infrastructure deployed via Terraform with CI/CD automation

Tech stack


🏭 Forge-Ops

Agentic Operational Intelligence Platform Β· Multi-Agent Orchestration

An industrial-grade multi-agent system that bridges technical documentation, live SQL databases, and operational signals to generate actionable mitigation strategies in energy, logistics, and infrastructure environments.

Core architecture

  • Agent A (Librarian – RAG): searches manuals and safety SOPs via Kendra/OpenSearch
  • Agent B (Analyst – SQL): converts natural language into SQL queries for Athena/RDS
  • Agent C (Strategist – Reasoning): synthesizes outputs into structured recommendations
  • Orchestrator: AWS Step Functions coordinating agent workflows and escalation logic

Industry-grade capabilities

  • Human-in-the-loop approval before high-cost actions
  • Cost guardrails integrated with TokVigil
  • Multi-agent tool calling via AWS Bedrock
  • Secure IAM role-based access with least privilege
  • Secrets stored in AWS Secrets Manager
  • Infrastructure fully deployed using AWS CDK

Tech stack


🧠 Core Technical Focus

🧩 Programming Languages

  • Python
  • TypeScript
  • JavaScript
  • Go

πŸ—„οΈ Databases & Storage

  • PostgreSQL
  • MySQL
  • MariaDB
  • Microsoft SQL Server
  • MongoDB
  • Amazon DynamoDB
  • Amazon Aurora
  • Amazon S3
  • Redis
  • pgvector

🌐 Backend, APIs & Frameworks

  • FastAPI
  • Django
  • Node.js
  • Express.js
  • NestJS
  • REST APIs
  • WebSockets
  • Background workers and async processing
  • Go (backend services)

🎨 Frontend & UI

  • React
  • Next.js
  • Component-based UI architecture
  • Server-side rendering and performance optimization

🧠 Machine Learning & Data

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • XGBoost
  • MLflow
  • Pandas
  • NumPy
  • Time-series forecasting and regression models

☁️ Cloud, DevOps & MLOps

  • AWS (EC2, S3, RDS, ECS, Lambda, SageMaker)
  • Docker
  • Kubernetes
  • GitHub Actions
  • Infrastructure as Code (Terraform)
  • Monitoring, logging, and cost optimization

βš™οΈ What I Deliver

  • End-to-end systems from idea to architecture to production
  • Scalable, cloud-ready, AI-powered platforms
  • Clean, maintainable, and well-documented code
  • Reliable execution and clear communication

πŸ“Š GitHub Activity

GitHub Contribution Graph


πŸ§ͺ Problem Solving


πŸ“« Connect

Pinned Loading

  1. Nordict Nordict Public

    Cloud-native multi-horizon market forecasting platform with probabilistic predictions, confidence scoring, and production-grade ML infrastructure.

    TypeScript 1

  2. TokVigil TokVigil Public

    Application-layer AI usage control platform with SDKs and a policy engine to enforce budgets, limits, and audit logs per user, feature, and plan.

    TypeScript

  3. Masters-Thesis-Regional-Wildfire-Forecasting-AI Masters-Thesis-Regional-Wildfire-Forecasting-AI Public

    Master’s Thesis (2025): Data processing, model training, hyperparameter tuning, and evaluation for Regional Scale Wildfire Occurrence Forecasting Through AI Techniques. Includes implementations of …

    Jupyter Notebook

  4. Extreme-Whether-Event-Prediction Extreme-Whether-Event-Prediction Public

    Predicting wildfires using LSTM neural networks and ARIMA models based on historical data to improve wildfire forecasting accuracy.

    Jupyter Notebook 1

  5. R-Hydrological-Analysis R-Hydrological-Analysis Public

    R-based hydrological analysis of the Savinja River catchment (Veliko Ε irje station), covering data preparation, basic analysis, low-flow and flood frequency analysis, and hydrological modeling usin…

    HTML 1

  6. Python-telegram-referral-bot Python-telegram-referral-bot Public

    A Telegram bot built with Python for managing referral systems, tracking invites, and displaying leaderboards.

    Python 1