Software Engineer at Physics Wallah
Backend and systems engineer at Physics Wallah, pursuing a BSc in Data Science and AI at IIT Guwahati. Focused on scalable architectures, database security, and AI-enabled products.
Backend
Architecture-first engineering
Scale
Systems that hold under load
AI
Product thinking with AI systems
About
I’m a backend engineer focused on building scalable systems and designing reliable software architectures. I’m currently a Backend and Systems Engineer at Physics Wallah and pursuing a BSc in Data Science and AI at IIT Guwahati. I started with competitive programming, which sharpened problem-solving instincts, and moved into system design, distributed workflows, and AI-powered applications.
I like backend systems that communicate intent clearly: fewer moving parts, sharper boundaries, and reliable behavior under load.
My work lives at the intersection of APIs, distributed workflows, and product-aware engineering. I care about the full path from request to response as much as the architecture that supports it.
Node.js/Express
Quiet APIs that stay stable under load.
TypeScript
My safety net when things start to grow.
System Design
I like breaking chaos into smaller rooms.
Distributed Systems
Where scale gets real and tradeoffs show up.
API Design
A good contract should feel obvious.
Caching
I reach for it when the path starts to feel heavy.
Queues
Useful when work needs breathing room.
Databases
Designing schemas and queries that scale with usage.
Observability
Understanding systems through logs, metrics, and traces.
Backend
Architecture-first engineering
Scale
Systems that hold under load
AI
Product thinking with AI systems
Work
A vertical timeline that focuses on how I think about production software rather than just listing tasks.
Systems
The diagram stays sticky while the narrative unfolds on the left. Each step highlights a distinct layer of the request lifecycle, from user input to scaling behavior.
Architecture diagram
User
01API Gateway
02Queue + Workers
03Database
04Response Flow
05Scale Out
06Projects
Each scroll segment surfaces the problem, the response, the system shape, and the outcome. These are temporary placeholders you can edit later from the projectSegments array.
Project segment
Problem
Large-scale search latency made retrieval feel slow and inconsistent.
Solution
Optimized indexing and query shaping to keep retrieval focused and fast.
Architecture highlight
API -> Search Layer -> Database
Impact
Reduced latency and improved the usability of history-heavy workflows.
Active project
FocusedSignal
Project segment
Problem
Incoming work needed to be processed quickly without blocking the user path.
Solution
Split the flow into queue-driven workers with clear back-pressure.
Architecture highlight
API -> Queue -> Worker Pool -> Persistent Store
Impact
Kept the request path lightweight while scaling background execution.
Active project
FocusedSignal
Project segment
Problem
AI features needed a stable integration model, not a fragile demo layer.
Solution
Added guardrails, deterministic fallbacks, and response shaping.
Architecture highlight
Client -> Orchestrator -> Model + Cache + Policy Layer
Impact
Delivered useful AI capabilities with production discipline.
Active project
FocusedSignal
Project segment
Problem
Notification spikes caused retries, duplicate sends, and delayed delivery.
Solution
Introduced idempotent workers and batched dispatch with retry policies.
Architecture highlight
API -> Queue -> Worker -> Provider Adapters -> Logs
Impact
Improved delivery consistency and reduced duplicate notification events.
Active project
FocusedSignal
Contact
If you’re working on interesting systems or need help building scalable backend solutions, feel free to reach out.