Most organisations can get an AI demo working. Fewer can get one to production that performs under real load, survives a security audit, and holds up at 5M+ users. That gap — between demo and production-grade — is where I spend my time.

I design and lead platforms that don't just work in a boardroom presentation. They perform under real pressure, real edge cases, and real regulatory scrutiny — across teams, time zones, and cloud providers.

Making AI trustworthy in production.

That means building the observability, governance, and platform guardrails that sit between an LLM demo and a real production system:

• 🔍 LLMOps & Observability — RAG pipelines, vector search, embeddings, Langfuse + OpenTelemetry for model monitoring
• 🔐 AI Governance — PII protection, data privacy, compliance frameworks that survive audits
• 🚀 AI Platform Engineering — Automated LLM deployment via CI/CD, Docker, Helm, ArgoCD
• 🔗 Hybrid LLM Integrations — OpenAI, Claude, LLaMA, Ollama at enterprise scale

These repositories reflect my actual platform engineering work. Each one is a reference implementation, not a tutorial clone.

Principal Architect
│
├── Platform Engineering
│     ├── Internal Developer Platforms (IDPs)
│     ├── Kubernetes-first golden paths
│     ├── GitOps (ArgoCD · Flux)
│     └── Infrastructure as Code (Terraform · Ansible)
│
├── Cloud Architecture
│     ├── Multi-cloud strategy (AWS · GCP · Azure)
│     ├── Event-driven & serverless systems
│     ├── FinOps governance & cost optimisation
│     └── Multi-region HA/DR design
│
├── DevSecOps & Security
│     ├── Zero Trust architecture
│     ├── SAST · DAST · SCA automated pipelines
│     ├── ISO 27001 & SOC2 compliance
│     └── Threat modelling at design stage
│
└── AI/LLM Platform Engineering
      ├── RAG pipelines & vector search
      ├── LLMOps observability & governance
      ├── Hybrid LLM integrations
      └── AI compliance & PII protection

I believe great engineers share what they know. Here is where I do that:

• 📺 YouTube DevOps Course — A 7-course, 69-session production DevOps + DevSecOps curriculum I am building openly. From Linux Foundations to Capstone Platform Engineering.
• 📝 Architecture Decision Records — Every major design choice in my public repos includes an ADR explaining context, alternatives considered, and consequences.
• 💡 LinkedIn — I write about platform engineering, AI governance, and hard-won lessons from enterprise architecture. Follow here.

I work best with global, distributed, async-first teams. The best architecture decisions I have been part of happened across time zones — driven by clear written thinking, not just whiteboards.

I am open to conversations about:

• Platform engineering at scale
• AI infrastructure and LLMOps
• Cloud security architecture
• Technical leadership and architecture governance
• Speaking & teaching — conferences, workshops, YouTube collaborations