I am a graduate student with 2.5 years of production experience building scalable backend systems. Previously at Tekion Corp, I helped engineer financial pipelines that processed millions of transactions.

Currently, I am deep-diving into Distributed Systems and AI, building projects like low-latency trading engines and real-time telemetry streams. I am passionate about writing clean, concurrency-safe code and am looking for Internship / New Grad opportunities to apply these skills at scale.

I believe in choosing the right tool for the job. Here is the stack I use to build reliable, high-performance software:

Domain	Stack & Patterns
Distributed Systems	Event-Driven Architecture, Pub/Sub, Protobuf
Core Languages	Object-Oriented Design, Concurrency, Algorithms
AI & ML Engineering	Multi-Agent Systems, RAG, LLM Integration
Data & Storage	Time-Series, Spatial Indexing, Caching Strategies
Infrastructure

"Processing 10,000 events/second with sub-5ms latency."

A distributed system designed to ingest and visualize massive sensor data streams from electric vehicle fleets.

• Architecture: Go workers consume gRPC streams and fan-out to Apache Kafka.
• Scale: Handles 1,000+ concurrent connections using buffered channels and worker pools.
• Data: Persists high-velocity data to InfluxDB for time-series analysis.
• Frontend: Next.js dashboard with Server-Sent Events (SSE) for live tracking.

"Zero-GC, Lock-Free Concurrency."

A production-grade Central Limit Order Book (CLOB) designed for financial markets, prioritizing microsecond latency over convenience.

• Performance: Achieved 0 bytes/op allocation rate on the hot path using Object Pooling.
• Concurrency: Implemented Lock-Free data structures (StampedLock) and atomic primitives.
• Optimization: Custom intrusive linked lists to eliminate JVM object overhead.

"Where Blockchain meets Computer Vision."

A trustless gig-economy platform combining Smart Contracts with AI verification to automate payments.

• Blockchain: Neo N3 Smart Contracts hold funds in escrow until verification.
• AI Verification: GPT-4 Vision analyzes "Proof of Work" photos to auto-approve releases.
• Reliability: Exponential backoff WebSocket handling and startup recovery for pending transactions.
• Tech: Python (FastAPI), Solidity/Boa3, Next.js, Docker.

"Orchestrating AI Agents like microservices."

A distributed planning system where specialized AI agents (Food, Transport, Activity) collaborate to build itineraries.

• Design: Decoupled Spring Boot (Core) and Python (AI) services via RabbitMQ.
• AI: Uses CrewAI and Google Vertex to manage hierarchical agent delegation.
• Validation: Implemented strict Pydantic models to force LLMs to output structured, valid JSON.