Sparsh Birla
Backend-focused developer with experience in asynchronous event handling, distributed systems patterns, and retrieval-augmented generation pipelines.
Performance across four engineering signals.
What the signals reveal
Experience building production-grade alerting engines with asynchronous task queues, sliding-window rate limiting, and dead-letter queue isolation. Implementation work includes RAG-based application systems utilizing vector databases and LLM integrations.
Quantified signals
Numbers pulled directly from connected sources. Refreshed every 12 hrs.
What's actually been shipped
Auto-detected from GitHub. Tech stack inferred. AI summaries generated.
RAG and LLM based personal assistant
RAG based Chatbot that generates LinkedIn profile data and answers questions based on person profile featuring use of LangChain and LLamaIndex.
No repository description available.
A production-grade, event-driven alerting engine built with FastAPI, Celery, Redis, and PostgreSQL. Demonstrates core distributed systems patterns including async task queues, deduplication, sliding-window rate limiting, exponential backoff, dead-letter queues (DLQ), and automated AI storm digests.
The work, indexed.
Activity across public repositories and open-source contributions over the last 12 months.
Problem-solving signal
Numbers pulled directly from LeetCode. Contest performance and problem-solving activity analyzed.