Hi, I'm Nasit Sony 👋

💡 AI Infrastructure Engineer | Distributed Systems | Consensus Protocols (BFT)
📍 Building production-grade backend systems for AI and fault-tolerant distributed computing

I build distributed backend systems where correctness matters — even under failures, partitions, and adversarial conditions.

My work sits at the intersection of:

• AI infrastructure
• Distributed systems engineering
• Byzantine fault-tolerant consensus

I focus on treating AI systems not as simple APIs, but as fault-tolerant distributed systems with strong correctness guarantees.

💰 Production Systems (Fintech)

• Built international money transfer systems handling $600M+ annual volume
• Focus: correctness, consistency, and performance under real-world constraints

🔬 Distributed Systems & BFT Research

• Published work in Springer journals and international conferences
• Designed and implemented Byzantine fault-tolerant protocols
• Bridging theoretical guarantees with practical system design

🚀 Current Focus — AI Infrastructure

• Building production-grade AI pipelines (SmartSearch)
• Applying distributed systems thinking to RAG and ML systems
• Exploring decentralized and fault-tolerant ML infrastructure

Production-oriented AI system built like real backend infrastructure.

Key Features:

• Asynchronous ingestion (Kafka → Workers → PostgreSQL)
• Embedding-based semantic search (pgvector + OpenAI)
• Retrieval-Augmented Generation (RAG)

Reliability Engineering:

• Idempotent processing (no duplicate chunks)
• Retry + DLQ handling
• Worker crash recovery (offset-safe Kafka processing)
• Explicit lifecycle tracking (PENDING → PROCESSING → READY/FAILED)
• Eventual consistency guarantees

👉 Focus: AI systems as distributed systems

Backend infrastructure system focused on security, scalability, and reliability.

• JWT & OAuth2 authentication
• Request routing and service orchestration
• Observability and failure handling

Storage engine inspired by LSM-tree designs (RocksDB-style).

👉 Focus: durability, compaction, and performance trade-offs

Fault-tolerant distributed system inspired by Raft and BFT protocols.

👉 Focus: safety, liveness, and failure handling

Languages:
Java, Rust (learning), Python

Backend & Infra:
Spring Boot, Kafka, PostgreSQL, pgvector

AI Stack:
Embeddings, RAG pipelines, OpenAI APIs

Distributed Systems:
Consensus, fault tolerance, idempotency, retries

• Prioritized-MVBA — Optimal Asynchronous Byzantine Agreement Protocol
• Published in Springer journals & international conferences
• Google Scholar: https://scholar.google.com/citations?user=mBIQ1-0AAAAJ&hl=en

• Medium: https://medium.com/@nasitsony96
• Topics:
  • Failure handling in async systems
  • Idempotency and retries
  • Designing production-grade RAG systems

• AI infrastructure & reliability
• Fault-tolerant distributed systems
• Consensus protocol engineering

• LinkedIn: https://www.linkedin.com/in/nasitsony

⭐ I believe systems should be designed for failure — not just success.