Building Sovereign, Secure & Production-Grade AI Systems
Bridging the gap between cutting-edge AI capabilities—Multimodal, Agentic RAG, Autonomous Workflows—and enterprise-grade safety, sovereignty & ethics.
📖 Read also: AI Engineer role
How I Build with AI — The 4 Engineering Pillars
Delivering measurable product value through robust architecture, security, and user experience
Agentic Orchestration & Workflows
Designing autonomous agents capable of planning, tool/API execution, and multi-step tasks with deterministic reliability and structured fallbacks.
Enterprise & Advanced RAG
Hybrid search architectures (semantic, vector, BM25, reranking, Knowledge Graphs) guaranteeing precise, zero-hallucination domain knowledge retrieval.
Security, Ethics & Sovereignty
Deploying sovereign AI (Local/Open-Source LLMs, private cloud), zero PII data leaks, hard guardrails, and compliance with European regulations (EU AI Act).
Multimodal & Real-World Interaction
Integrating vision and audio models with robotics gateways to extend AI beyond text into reactive, physical, and real-time interaction.
Technical Stack & Architecture Matrix
Production-tested tools and frameworks organized by engineering layer
| Engineering Domain | Technologies & Frameworks |
|---|---|
| Orchestration & Agents |
LangGraph
LlamaIndex
CrewAI
AutoGen
MCP Protocol
|
| RAG & Vector DBs |
Qdrant
Pinecone
pgvector
BM25 / Hybrid Search
Cohere / BGE Rerankers
|
| Sovereignty & LLMs |
Ollama
vLLM
Hugging Face
Fine-Tuning (LoRA)
Llama 3 / Mistral / Kimi
|
| Evaluation & Safety |
LangSmith
Ragas (Evals)
NeMo Guardrails
Presidio (PII)
detect-secrets
|
| Engineering & Product |
Python
TypeScript
FastAPI
Docker Multi-Stage
Cloud (GCP / AWS)
|
AI Product Case Studies & Demos
Enterprise-ready intelligent applications built for real-world impact and strict safety
Automatic i18n JSON Translator
Problem: Software localization corruption on interpolation variables.
Architecture: FastAPI microservice, Pydantic Structured Outputs, Regex protection & atomic disk checkpointing.
Impact: 100% variable safety, 0 key loss, deployed on Cloud Run.
AI Product Engineering Blueprint (AIPE)
Problem: Initial technical debt and security leaks in AI projects.
Architecture: Poetry isolation, Ruff linter/formatter, Mypy strict (100%), non-root multi-stage Docker & pre-commit gatekeeping.
Impact: Developer onboarding < 5 min, 64/64 tests passed.
Automated AI Watcher CLI (Wrapper_CLI)
Problem: Heterogeneous AI technological surveillance & uncontrolled LLM API costs.
How it works: Multi-source ingestion (Text, Files, Web URLs), automated LLM analysis, FinOps pricing engine (40+ LLMs), Tenacity exponential backoff & SHA-256 caching.
Impact: Instant multi-format reports (Console, JSON, Markdown), zero-cost offline demo mode.
Multi-Agent Workflow Orchestrator
Problem: Complex multi-step task execution requiring dynamic tool calling.
Architecture: CrewAI & AutoGen agent network with WebSockets and FastAPI event loop.
Impact: Distributed decision making with deterministic state rollbacks.
Vision AI & Analytics Microservice
Problem: Multimodal document processing and visual anomaly detection.
Architecture: PyTorch & OpenCV pipeline integrated with Gemini Vision API.
Impact: Real-time OCR and visual semantic extraction.