Alex Christopher.
I am a GenAI Engineer turning paper methodologies into production realities. I orchestrate LLMs, engineer agents, and build scalable infrastructure.
Work Experience
Agentic RAG-powered Test Report Generator
PRODUCTION APPLICATION
Built and productionized a multi-agent RAG pipeline that automatically retrieves performance run metrics, aligns them with historical baselines, and synthesizes insights via LLM-driven orchestration across a LangGraph agent graph.
A dedicated Validator Agent runs after each LLM generation step, cross-checking the output against structured baselines and schema rules before the final report is assembled—ensuring zero-hallucination, production-grade accuracy.
Delivered complete reports in PDF/Word/email formats, shrinking turnaround from 2 hours to 15 mins. Adoption by 5+ QA teams reduced manual reporting workload by 60%.
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AI-assisted Apache JMeter Engine
TESTING AUTOMATION
Architected a scripting engine that auto-correlates dynamic parameters and templatizes datasets for reuse, reducing average script build time by 60%.
Automated correlation pipelines combining rule-based extractors with LLM verification to eliminate repetitive trial-and-error debugging.
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AI-driven Accessibility Remediation Engine
ACCESSIBILITY & COMPLIANCE
Built an AI-driven Accessibility Remediation Engine using Playwright and axe-core to automatically audit webpages, detect WCAG 2.1 compliance issues, and generate production-ready remediation code via LLMs.
Ensured all LLM-generated fixes preserved existing UI structure and adhered to organization-approved color standards, enabling faster, consistent accessibility compliance across web applications without manual intervention.
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Personal Projects
Multi-Agent Framework
JAN 2025 - PRESENT
Designed a lightweight framework where AI agents collaborate to plan, generate, and validate tasks using open-source LLMs to enhance security.
Python Library AI Assistant
AUG 2025 - PRESENT
Developed a RAG assistant using LangChain to deliver contextual code support, integrating OpenAI embeddings and ChromaDB.
Auto ML Generation (OSS)
Open SourceJAN 2023 - APR 2023
An open-source Python package that automates the entire machine learning workflow end-to-end. Feed it a raw CSV and it handles EDA, feature engineering, model selection (across classifiers/regressors), cross-validation, and hyperparameter tuning automatically—outputting a production-ready, serialized model. Designed to remove the repetitive boilerplate from ML experimentation and let engineers focus on problem framing instead.
GenAI Engineer Portfolio — This Site
Open SourceMAR 2025 — OPEN SOURCE
The very portfolio you are viewing, built as an open-source project. Features a Python-themed typing animation, Framer Motion physics-based tech stack reveals, a terminal system initialization sequence, and a code-aesthetic dark design system. Fork it, adapt it, make it yours.
Research & Implementations
Attention is All You Need.py
A complete, ground-up Python recreation of the seminal Transformer architecture paper. Implemented multi-head self-attention mechanisms, positional encoding matrices, and feed-forward networks purely from scratch to deeply understand the mechanics of modern LLMs.
View Source Code