AI Development & Automation
Hands-on experimentation with Python, AI-assisted workflows, local language models, and agent-based automation.
Technical leader with 10+ years of infrastructure engineering experience spanning enterprise IT, SaaS ecosystems, and deep systems analysis. Expert at root cause investigations, API debugging, infrastructure topology visualisation, and designing automated workflows that reduce manual ticketing overhead by 33%.
Originally from Sheffield, England, I made Aliyah to Israel in 2014, and Israel is now home. Family is a big part of my life, and outside work I enjoy spending time with my family, reading, and continuing to learn new things.
I'm naturally curious about how things work and enjoy getting hands-on with technology. My homelab is where I can experiment, explore new ideas, and learn by building. From virtualisation and Proxmox to Docker, self-hosted services, monitoring, automation, and local AI models, I enjoy bringing different technologies together to build a connected, reliable environment. I tend to take a practical, logical approach to challenges: understand the problem, experiment with solutions, and keep refining until things work as they should.
Looking ahead, I'm particularly interested in exploring more advanced automation and AI projects, finding new ways to make systems smarter and everyday tasks simpler. When I'm not tinkering with technology, you'll often find me following Sheffield Wednesday and England in football, or Yorkshire and England in cricket.
I'm building on my infrastructure and troubleshooting background through practical AI development projects, with a particular interest in AI security and early-stage product teams.
Hands-on experimentation with Python, AI-assisted workflows, local language models, and agent-based automation.
Developing security knowledge through SecAI courses and practical labs, supported by experience with access controls, secure remote access, and troubleshooting integrations.
A practical engineering foundation for investigating behaviour across applications, APIs, logs, networks, and Linux-based environments.
The monitoring demo now routes synthetic Prometheus alerts through Alertmanager into Alerta and records resolved alerts. A separate read-only homelab AI agent is in development; autonomous diagnosis and self-healing remain planned.
A mix of professional engineering experience and hands-on personal projects. Project-based AI and machine-learning skills are presented as practical development experience, not as years of commercial AI employment.
Building and troubleshooting Python applications and small web apps, including Flask and Streamlit projects.
Project work includes a loan-approval prediction application and clustering experiments, including model retraining and cluster evaluation.
Experimenting with local LLMs and API-based model access, and developing a modular agent with tool integrations, configuration, retrieval, memory, and documentation capabilities.
Professional experience diagnosing integrations and project experience building and testing application components.
Hands-on homelab experience operating services and building monitoring and logging across virtualised and containerised environments.
Experience with access controls, secure remote access, incident investigation and recovery documentation; developing AI security skills through study and practical labs.
Pick a time that suits you for an introductory call or an interview. Bookings go straight into my calendar.