AI & Security Engineering
I build AI. I also break it.
Six years across AI and security engineering, the last two leading a team of ten. Most days I'm building agentic LLM pipelines with LangGraph (Python or TypeScript) and shipping them on AWS, Azure or GCP with the MLOps wiring that goes with it: experiment tracking, model versioning, observability across the lifecycle. The other half of the job: red-teaming LLM systems against the OWASP LLM Top 10 with tools such as Garak or Promptfoo, and wiring DevSecOps into the CI/CD.
Featured writing
Engineering & research
- ai 2 min read
Building RedTeam MCP: An AI-Powered Penetration Testing Assistant
A practical guide to building an MCP server that enables AI assistants to orchestrate offensive security tools for penetration testing, with proper safety guardrails
Read article - langchain 3 min read
Building LangChain Tools and Agents: From Zero to SOAR Assistant
Learn how to create LangChain tools from scratch and build a simple SOAR (Security Orchestration, Automation and Response) agent. This hands-on tutorial covers the fundamentals of tool development and agent creation for security automation.
Read article - rag 5 min read
Building a RAG System for Cybersecurity Compliance: A Simple POC with LangChain v1+
A step-by-step walkthrough of building a basic RAG system with LangChain v1+ to query compliance regulations. This is an unoptimized POC for learning purposes, not production-ready.
Read article - langgraph 5 min read
LangGraph Agent Architectures and Patterns: A Professional Guide
A comprehensive theoretical guide on agent architectures and patterns used professionally in AI projects. From simple workflows to hierarchical multi-agent systems, with real-world use cases for each pattern.
Read article - ai 6 min read
Model Context Protocol (MCP): Bridging the Gap Between AI and External Systems
An in-depth exploration of Model Context Protocol (MCP), the open standard revolutionizing how AI systems interact with external data sources and tools
Read article - adversarial-ml 14 min read
Adversarial Machine Learning: Attacks and Defenses
Deep dive into adversarial attacks against ML models: evasion, poisoning, and extraction. Exploring defenses, red teaming strategies, and the MITRE ATLAS framework for securing AI systems.
Read article - embeddings 7 min read
Vector Embeddings and Semantic Search: The Foundation of Modern AI
A comprehensive exploration of vector embeddings, from word2vec to modern transformers, and how they enable semantic search in production systems
Read article - llm 8 min read
Understanding LLM (Large Language Models): From Transformers to GPT
A deep dive into the architecture, mechanisms, and evolution of Large Language Models, from the Transformer breakthrough to modern GPT systems
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Latest posts
All posts →- Elastic ML 12 min read
Engineering Security ML with Elastic – Part 4: Production Pipelines with Dagster & MLflow
Transitioning from exploratory notebooks to reliable, repeatable anomaly detection pipelines using Dagster and lightweight MLflow-based model management.
Read article - ml-cyber 20 min read
Engineering Security ML with Elastic – Part 3: Benchmarking Unsupervised Models
How to Compare Anomaly Detection Models Without Labels
Read article - elasticsearch 16 min read
Engineering Security ML with Elastic – Part 2: Unsupervised Anomaly Detection
Learning Normal Authentication Behavior with Autoencoders
Read article - elasticsearch 11 min read
Engineering Security ML with Elastic – Part 1: From Logs to Features
From Windows Event Logs to Behavioral Features: Preparing Elasticsearch Data for Anomaly Detection
Read article - typescript 3 min read
TypeScript for Pythonistas: A Guide to Building Red Team Tools
A comprehensive TypeScript guide for Python developers. Learn the fundamentals by comparing Python and TypeScript code, focused on offensive security tool development and MCP servers.
Read article - docker 2 min read
Docker & Kubernetes Abuse Cheatsheet
Container escapes, docker.sock exploitation, K8s privilege escalation and misconfigurations for HTB, CTFs and cloud pentests
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