I build production-grade AI systems and scalable backend infrastructure — combining generative AI, intelligent automation, distributed systems, and strong software engineering fundamentals.

Currently, I'm working at DP World, building scalable systems for global trade. Previously, I worked at Amazon, building high-throughput data and backend systems.

My current focus is at the intersection of AI Engineering + Backend Engineering: turning LLMs and AI agents into reliable, observable, production-ready systems.

• 🤖 AI Applications — LLM-powered systems, RAG, AI agents & intelligent automation
• 🔎 Retrieval Systems — embeddings, vector search, semantic retrieval & pgvector
• ⚙️ AI Infrastructure — integrating AI capabilities into production backend systems
• 🎙️ AI Agents — exploring voice agents, tool calling & agentic workflows
• 🚀 Backend Systems — scalable microservices, APIs & event-driven architectures
• 📡 Distributed Systems — Kafka, asynchronous processing, caching & high-throughput services
• ☁️ Cloud Engineering — AWS, Azure & cloud-native architectures

I'm particularly interested in building AI systems that go beyond simple LLM calls.

Current areas of exploration:

LLMs · RAG · AI Agents · Embeddings · Vector Search · Prompt Engineering
Tool Calling · Agentic Workflows · Voice AI · LLM Evaluation · AI Automation

One of my recent projects is an AI-powered incident troubleshooting system that combines production knowledge, embeddings, vector search and LLMs to help engineers investigate and resolve incidents faster.

I bring nearly 5 years of backend engineering experience building production systems across logistics, fintech and large-scale platforms.

Core strengths:

Java · Spring Boot · Python · Kafka · PostgreSQL · Redis
Microservices · REST APIs · Distributed Systems · System Design · Event-Driven Architecture

I care about the engineering underneath AI systems too — latency, reliability, scalability, observability, concurrency and clean architecture.

AI & Intelligent Systems

LLMs RAG Embeddings Vector Search AI Agents Azure OpenAI pgvector

Backend & Distributed Systems

Microservices Kafka REST Distributed Systems System Design

Data & Messaging

PostgreSQL MySQL Redis Vector Databases Event Streaming

Cloud & Infrastructure

AWS Azure Docker Kubernetes CI/CD DevOps

Observability & Engineering

Monitoring Performance Engineering Production Debugging DevSecOps

AI is powerful. Production AI needs great engineering.

I enjoy working on problems where AI meets real-world systems — building the intelligence layer while making sure the underlying system is scalable, reliable and maintainable.

I’m especially interested in:

AI Agents → Tool Calling → Retrieval → Backend Services → Event Streams → Production

I'm always interested in collaborating on projects involving:

AI Agents • LLM Applications • Voice AI • Developer Tools • Distributed Systems • Backend Infrastructure

If you're building something ambitious at the intersection of AI and software engineering, let's connect.

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