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Htunn Thu Thu

Principal Architect · GenAI & AIOps · Platform Engineering

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About

Principal Architect & Advisor with 10+ years of leadership at the intersection of high-velocity cloud platforms, automated security, and data ecosystems. I translate complex technical innovation — GenAI, AIOps, agentic systems, and LLMOps — into resilient corporate infrastructure that drives business growth while maintaining strict enterprise governance.

My career is defined by spearheading organization-wide transformations, establishing global engineering standards, and acting as a technical force multiplier — bridging executive leadership and engineering teams to balance innovation with regulatory compliance.

As an active open-source author, I build tools that automate compliance, streamline platform delivery, and securely integrate AI with enterprise infrastructure.


What I Do

 GenAI, Agentic Systems & AIOps

  • Secure platforms across the full AI lifecycle — LLMOps, MLOps, governance
  • Agentic systems with tool use, planning, memory & human-in-the-loop
  • Model Context Protocol (MCP) servers and multi-channel AI agents
  • Multi-provider LLM strategy — Azure OpenAI, OpenAI, GitHub Models, Anthropic, Gemini, Ollama
  • RAG, fine-tuning, evaluation, and guardrails for production workloads
  • AIOps for Kubernetes — detection, RCA, automated remediation

 Platform Engineering, IDPs & SRE

  • Self-service Internal Developer Platforms that boost developer velocity
  • Vendor-agnostic multi-cloud strategy across AWS & Azure (Terraform, Ansible)
  • Container orchestration and service mesh at enterprise scale
  • SRE practices — SLOs, error budgets, golden paths, paved roads
  • Cost optimization and operational resilience at scale

 Enterprise DevSecOps

  • Organization-wide secure pipelines and compliance automation (IM8, OWASP, CIS, NIST)
  • Supply-chain security (SBOM, SAST/DAST, SCA) — 60%+ MTTR reduction
  • Cloud security: CSPM, CWPP, CNAPP, ZTNA, SASE
  • AI/LLM threat modeling — OWASP LLM Top 10
  • Zero-trust IAM and passwordless authentication

 Engineering Leadership & OSS

  • Technical authority across distributed global business units
  • Mentor senior engineers; build SRE and security cultures
  • Author OSS tooling that removes dev↔ops friction
  • Translate strategy for C-suite while staying hands-on with architecture

Selected Open Source

Production-grade tools at the intersection of AI, security, and platform engineering — designed to be deployed inside real enterprises.

Project Description Stack
simple-ai-agent Production-ready multi-channel AI agent — AIOps, Kubernetes management, security scanning, human-in-the-loop remediation. Built on FastAPI, GitHub Models, and MCP. Python · FastAPI · MCP
simple-cicd-translator Agentic service translating CI/CD pipelines between Jenkins, GitLab CI, and GitHub Actions via pluggable LLMs (Gemini, OpenAI, Azure OpenAI, GitHub Models, Anthropic, Ollama). Python · Multi-LLM
simple-exploit AI-powered pentest framework with hot-reloadable plugins, intelligent WAF bypass, and dual AI engines — GitHub Models (GPT-4o/5) and Ollama (Gemma/Llama 3, offline). Go · Ollama
ansible-inspec Combines Ansible automation with Chef InSpec for continuous compliance and security validation. Python
simple-waf-scanner High-performance WAF detection and authorized security testing toolkit, written in Rust. Rust
simple-service-bus Decentralized ESB with multi-protocol support (HTTP, gRPC, AMQP, MQTT, Kafka, WebSocket, GraphQL) — useful infrastructure for agent-to-agent messaging. Go · TypeScript
simple-faceid Face recognition and identification system with advanced computer vision capabilities for secure authentication. Python · OpenCV
simple-port-checker Python tool for firewall port checking and L7 protection detection (WAF, CDN). Python
ml-training Machine learning from the ground up — mathematics first, code second. NumPy · scikit-learn · Apple Silicon (ARM64 native). Jupyter · NumPy

Selected Impact

  • DevSecOps at scale — Authored automated supply-chain security (SBOM, SAST/DAST) across enterprise SDLCs, delivering 60%+ reduction in MTTR.
  • Multi-cloud strategy — Defined vendor-agnostic AWS + Azure architectures preventing lock-in while optimizing large-scale cloud spend.
  • Platform engineering — Built and scaled Internal Developer Platforms enabling self-service infrastructure, reducing deployment time by ~70% while maintaining security & compliance.
  • GenAI productionization — Translated AI research into governed enterprise systems with LLMOps, observability, and model risk management.
  • OSS authorship — Published production-grade tooling in Python, Go, and Rust spanning AI agents, compliance, and security testing.

Tech Stack

AI · GenAI · Agentic

ML · Data

Languages & Frameworks

Cloud & Platform

DevSecOps & Observability

Security & Compliance


GitHub Activity

Profile Details

Writing

I publish hands-on, production-tested writing at blog.htunnthuthu.comTech With Htunn:

  • GenAI & agentic systems — beyond demos to enterprise-ready architectures
  • LLMOps & AI security — prompt injection, data leakage, OWASP LLM Top 10
  • Platform engineering & SRE — IDPs, golden paths, paved roads
  • DevSecOps & multi-cloud — security as code, not afterthought

Let's Connect

Open to conversations on enterprise GenAI strategy, agentic platform architecture, LLMOps & AI security, IDPs, and multi-cloud transformation — and to OSS collaborations at the AI × platform × security boundary.


Translating frontier AI into governed, enterprise-grade platforms — secure, observable, and built to scale.

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