I'm a Backend & Systems Engineer who enjoys building systems from first principles.
My interests lie in:
- Distributed systems
- Backend infrastructure
- Systems programming
- AI agents & LLM tooling
I like exploring how systems actually work internally — networking, concurrency, protocols, and distributed coordination.
- Distributed systems design
- Building infrastructure tools in Go
- AI agents using LLMs
- Preparing for backend internships & GSoC
Understand systems, not just frameworks.
Build from first principles.
Learn by implementing real systems.
I enjoy building simplified versions of real-world infrastructure to understand how they work internally.
Examples:
| My Project | Inspiration(>Learning) |
|---|---|
| Distributed Job Queue | Celery / Kurbernetes |
| Distributed Grep | Google Distributed Grep |
| RedisInGO | Redis |
| Honeypot Detection Agent | Hackathon Project(ngl) |
| Data Visualisation Agent | AI data analyst tools |
- Distributed systems
- TCP networking
- Worker orchestration
- Message queues
- In-memory databases
- Redis internals
- Linux development environments
Backend Systems
│
├── Social Media Backend (Django)
│
Distributed Systems
│
├── Distributed Job Queue
├── Distributed Grep
│
Systems Programming
│
├── RedisInGO
│
AI Agents
│
├── Honeypot Detection Agent
├── Data Visualisation Agent
│
Developer Environment
│
└── Linux Config Files
🔗 https://github.com/ayush-github123/distributed-job-queue
A distributed task execution system to learn about Distributed Systems.
I wanted to understand how distributed workers coordinate tasks, detect failures, and process jobs in parallel across machines.
- Master-worker architecture
- Worker registration
- Heartbeat monitoring
- Task scheduling and dispatch
- Fault tolerance mechanisms
- Distributed scheduling
- Worker orchestration
- Failure detection
- Job execution pipelines
🔗 https://github.com/ayush-github123/distributed-grep
A distributed log search tool inspired by Google’s distributed grep design.
- Parallel search across multiple nodes
- TCP-based communication
- Master-worker coordination
- Aggregated results
- Distributed query execution
- Parallel processing
- Network communication
- Cluster coordination
🔗 https://github.com/ayush-github123/redisInGO
A Redis-like in-memory datastore built from scratch in Go.
To understand the internal design of high-performance in-memory databases.
- TCP server
- Command parser
- Key-value data store
- Redis protocol inspired interface
- Network servers
- Protocol design
- In-memory storage
- Concurrency handling
🔗 https://github.com/ayush-github123/honeypot-detection-agent
An AI-powered agent that analyzes Chats/Messages to detect honeypot scams via Chat and extract Intelligence from it.
- Message(s) analysis
- LLM reasoning pipeline
- Scam detection logic
- Risk evaluation
- AI agents
- Org/Private security
- Guardrails & JailBreaking
- Intelligence Extraction
🔗 https://github.com/ayush-github123/data-visualisation-agent
An LLM-powered analytics agent that generates insights and visualizations from datasets.
- Natural language queries
- Automated chart generation
- Data insight extraction
- LLM tool usage
- data analysis pipelines
- visualization automation
🔗 https://github.com/ayush-github123/social-media-backend
A scalable backend for a social media application.
- JWT authentication
- Posts, comments, likes
- REST APIs
- scalable backend architecture
- Django
- Django REST Framework
🔗 https://github.com/ayush-github123/my-linux-config-files
Personal configuration for a custom Arch Linux + Hyprland setup.
Includes configuration for:
- Hyprland window manager
- terminal environment
- development tooling
- productivity setup
Some things I've learned while building systems:
- Distributed systems fail in unexpected ways
- Network communication requires careful design
- Worker coordination is harder than it looks
- Observability is critical in distributed environments
- Simplicity often beats complex abstractions
