Abdelrahman Hegab
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Technical philosophy

Engineering

How I design, build, review, and evolve software systems across backend, frontend, architecture, delivery, and AI-assisted engineering.

Capability map

Engineering Expertise

A senior full-stack toolkit built over a decade of enterprise SaaS, government digital services, and production engineering.

  • Backend & Platform

    • C#
    • .NET / .NET Core
    • ASP.NET Core
    • REST APIs
    • Entity Framework / EF Core
    • Dapper
    • Microservices

  • Frontend

    • Angular
    • TypeScript
    • Vue.js
    • React
    • HTML
    • CSS / SCSS

  • Architecture & Distributed Systems

    • Software Architecture
    • Microservices
    • Distributed Systems
    • REST API Design
    • Clean / Onion Architecture
    • CQRS
    • Caching
    • Performance Optimization

  • Data

    • SQL Server
    • PostgreSQL
    • Data Modeling
    • Query Optimization

  • DevOps & Delivery

    • Docker
    • Kubernetes
    • Azure DevOps
    • Git
    • CI/CD
    • IIS

  • Engineering Leadership

    • Code Review
    • Mentoring
    • Technical Decision-Making
    • Feature Ownership
    • Architecture Guidance

  • AI-Augmented Development

    • Agentic coding workflows
    • AI coding agents
    • AI-assisted planning
    • Refactoring
    • Debugging
    • Testing
    • Code review
    • Technical documentation

Engineering approach

How I Engineer

The principles I use to make technical decisions, structure systems, and keep delivery maintainable as products and teams evolve.

  1. Architecture before accidental complexity

    Choose structures and patterns that solve real product and operational constraints while keeping the system understandable.

  2. Evidence-driven engineering

    Validate assumptions with requirements, system behavior, and tests before committing to a technical direction.

  3. Build for maintainability

    Use clear boundaries, readable code, appropriate abstractions, review, tests, and documentation to support long-lived systems.

  4. Security and production behavior matter

    Treat security, performance, reliability, and troubleshooting as part of engineering ownership from the start.

  5. Reusable infrastructure over repeated implementation

    Extract stable shared behavior when it reduces duplication while leaving business-specific rules with their features.

  6. Human ownership with AI acceleration

    Use AI to move faster while keeping architecture, validation, security, and final engineering decisions human-owned.

Modern engineering workflow

AI-Augmented Development

I use AI coding agents to accelerate research, technical planning, implementation, refactoring, debugging, testing, documentation, and code review while retaining human ownership of architecture, validation, security, business logic, and final engineering decisions.

Engineering Workflow

  1. Requirements
  2. Analysis
  3. Architecture
  4. Task Breakdown
  5. AI Assistance
  6. Validation
  7. Human Review
  8. CI/CD

Human Ownership

The following areas remain entirely human-owned at every stage of the workflow.

  • Architecture
  • Validation
  • Security
  • Business logic
  • Final engineering decisions

AI accelerates the work. Human judgment is responsible for correctness, security, and final engineering decisions.

Built for Production, Not Just Delivery

Good engineering is measured in systems that remain understandable, secure, and maintainable long after the initial delivery. The case studies below show this in practice.

View Selected Projects Contact Me