Let's Talk

From
requirements
to
working
systems.

I work across the full software lifecycle — understanding requirements, structuring solutions, supporting implementation, validating behavior, and bringing software through to delivery.

ANALYSIS DEVELOPMENT VALIDATION DELIVERY

Where ideas become systems.

April 2024 — Present

Eco Sourcing Hub Ltd

Software Engineer

United Kingdom · Remote

At Eco Sourcing Hub, I work across software engineering, system analysis, applied AI, testing, and delivery — turning business needs into structured requirements, clear implementation phases, and software that can be validated and delivered with confidence.

AI is deeply integrated into how I work. With a foundation in machine learning and AI concepts, I use AI across solution design, technical planning, implementation, debugging, validation, and delivery. I focus on understanding the systems I build while using modern AI tools to accelerate execution and explore stronger solutions.

  • System analysis & requirements definition
  • Software planning & delivery coordination
  • Testing, bug investigation & regression analysis
  • Security review & system hardening

Applied AI · AI-Assisted Engineering · System Analysis · Software Delivery · Security & Validation

May 2026 — Present

Vortex

Co-Founder & Software Engineer

At Vortex, I work across the full software lifecycle — from client requirements and system planning to implementation, testing, security review, deployment, and delivery.

AI is integrated throughout my engineering workflow — from analysis and solution design to implementation, debugging, and validation. I use it to accelerate exploration and execution with a focus on technical quality and coordinated delivery.

Across the
whole system.

From the first conversation to final delivery, each stage turns uncertainty into something clearer, buildable, testable, and ready to use.

  1. Understand

    Clarify client needs, workflows, constraints, and the real problem behind the request.

  2. Define

    Turn those needs into clear scope, requirements, roles, and expected system behavior.

  3. Structure

    Break the system into features, priorities, development phases, and actionable tasks.

  4. Build

    Guide implementation with engineering judgment and AI-assisted development where it adds value.

  5. Validate

    Test real workflows, investigate defects, and verify that the system behaves as intended.

  6. Secure

    Review sensitive flows, failure cases, and security risks, then harden what needs protection.

  7. Deliver

    Coordinate final validation, deployment, handoff, and the details needed for a usable release.

Earlier explorations.

My earlier work included academic machine-learning projects that helped shape the analytical side of how I approach software today.

  • Breast Cancer ClassificationGraduation Project · Machine Learning

    Developed and evaluated a machine learning classification model for identifying breast cancer cases based on structured input features.

  • Handwritten Digit RecognitionMachine Learning · Computer Vision

    Developed a machine learning model for recognizing and classifying handwritten digits from image inputs.

  • Sentiment AnalysisMachine Learning · NLP

    Developed and evaluated an NLP-based classification model for analyzing text and identifying sentiment.

Have a system
to figure out?

Bring the requirements.
We’ll find the structure.

Let’s Talk