Systems and AI Engineer specializing in autonomous agentic systems, local inference pipelines, and high-concurrency backends. Creator of AIBA, an open-source autonomous internet browsing agent driven by parallel swarms and spatial visual reasoning. Focused on bridging raw LLM capabilities with deterministic system design — architecting type-safe state machines and building strictly tested infrastructure for enterprise scale.
P_01
I'm driven by a fundamental need to understand how systems work internally. I deconstruct technologies to their core mechanics — "Why this design? What's the underlying math?"
This approach allows me to reason about complex architectures, optimize for performance, and build robust, scalable solutions from the ground up.
P_02
I design systems with maintainability, extensibility, and scalability in mind, applying SOLID principles to ensure clean, robust architectures.
This allows me to scale and refactor things easily on Friday when production is on fire ;), especially I love the plug-n-play design.
P_03
I focus on solving the problem at hand efficiently, avoiding unnecessary complexity while keeping the system flexible for future needs.
This ensures I can actually ship solutions instead of getting lost in over-engineering.
P_04
I prioritize understanding the real business goals before writing code, ensuring that the solutions I build deliver meaningful impact.
This allows me to think through the lens of the system's users.
A multi-agent consensus engine for decentralized compute allocation.
Python, FastAPI, PydanticAI, LangChain, MCP, A2A, TensorFlow, PyTorch, vLLM, GLINER, PySBD
Multi-agent orchestration, RAG pipelines, hybrid vector + sparse search, HITL guardrails, state-machine routing, Groq inference, Gemma, knowledge graphs
PostgreSQL (pgvector/HNSW), MongoDB, MySQL, Redis, TimescaleDB, InfluxDB
Docker, AWS, GCP, CI/CD (GitHub Actions), Grafana, Logfire, Pyright, Ruff, Pytest
MQTT, Modbus TCP, BACnet/IP, CoAP, Twilio, Plivo