§ III

About

I'm a First Class Computer Science graduate from Brunel University London, currently working as a Junior Data Scientist at EmergeIQ Ltd. My passion lies in building AI systems that solve real-world problems—from document intelligence and compliance verification to automated video analysis.

What drives me is the challenge of transforming messy, unstructured data into functional, reliable AI systems. I don't just build models; I engineer complete solutions with proper validation, security, and production-grade architecture. Every system I develop emphasizes thorough testing, OWASP LLM Top-10 compliance, and human-in-the-loop validation to ensure alignment with business requirements.

Beyond the technical work, I'm fascinated by the intersection of AI and practical problem-solving. Whether it's designing RAG pipelines for semantic search, implementing computer vision for video annotation, or developing agent-based workflow automation, I approach each project with a focus on reliability, security, and measurable impact.

§ IV

What I Do

  1. IOffering

    LLM Systems Engineering

    Design and build production-grade LLM applications with advanced prompt engineering, RAG architectures, and agent-based systems.

  2. IIOffering

    AI Security & Compliance

    Implement comprehensive security measures to protect AI systems from vulnerabilities and ensure regulatory compliance.

  3. IIIOffering

    Computer Vision Solutions

    Develop CV pipelines for video analysis, object detection, and automated annotation using modern frameworks.

  4. IVOffering

    Backend Development

    Build robust, scalable API backends with comprehensive authentication, validation, and monitoring.

  5. VOffering

    Document Intelligence

    Extract, analyze, and structure information from unstructured documents using AI-powered pipelines.

  6. VIOffering

    System Integration

    Connect AI capabilities with existing systems through well-designed APIs and integration patterns.

§ V

Approach

My approach to AI engineering is grounded in three core principles:

**1. Security First**: Every AI system I build incorporates security from the ground up—not as an afterthought. This means implementing prompt injection mitigation, input validation, output filtering, and achieving full OWASP LLM Top-10 compliance.

**2. Validation & Reliability**: AI outputs need systematic validation. I implement comprehensive testing frameworks to identify data gaps, contradictions, and logical inconsistencies before they reach production.

**3. Human-Centered Design**: AI should augment human capabilities, not replace human judgment. I design systems with controllability and human-in-the-loop validation, ensuring alignment with business requirements and user needs.

§ VI

Interests

Outside the terminal: ai research & innovation, open source contribution, problem solving, continuous learning.

Staying current with the latest developments in LLMs, RAG architectures, and AI security. I regularly explore new frameworks and methodologies to improve my craft.