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Software Engineer

Narasimharao
Bhavirisetty

Building real-time data pipelines, event-driven backend systems, and GenAI applications. Based in Bangalore, India.

About
Me

I'm a Software Engineer with 1.7+ years of experience building production-grade event-driven backend systems. I specialize in real-time data pipelines using Kafka, PyFlink, ClickHouse and Redis.

Most recently at Spizen Technologies, I worked on a Solana blockchain intelligence platform — building systems that processed live trading data, detected suspicious wallet behavior, and emitted real-time investment signals.

Previously at Algonox Technologies, I worked on backend automation, data cleaning pipelines, and user lifecycle management systems.

Outside work, I build and ship projects end-to-end — a RAG-based PDF Q&A system (LangChain, ChromaDB, Groq), a weather CLI published to PyPI, an ML flight-price predictor, and a real-time order notification service using Server-Sent Events. I'm focused on growing into AI engineering, where backend depth meets GenAI.

Technologies

Python Java Kafka PyFlink ClickHouse Redis MySQL PostgreSQL Flask Docker Kubernetes Grafana Loki Tempo RAG LangChain ChromaDB HuggingFace Groq AWS MSSQL Camunda Git Linux Pandas
Location
Bangalore, India
Open to relocation
Education
B.Tech — Computer Science
Tirumala Engineering College · 2020–2024 · CGPA 7.86
Email
narasimharao2743@gmail.com
Status
Open to Opportunities

Where
I've Worked

01
Spizen Technologies
Software Engineer · CLR3 Ventures · Bangalore
  • Built an end-to-end Solana token intelligence pipeline with multiple streaming jobs processing Pump.fun trade and graduation events through Kafka, ClickHouse, and Redis.
  • Designed PyFlink streaming jobs with tumbling window aggregations to deduplicate high-velocity blockchain trade data with fault-tolerant checkpointing.
  • Built a wallet bot classification system using behavioral analysis to identify suspicious trading patterns.
  • Engineered a real-time composite coin scoring engine incorporating wallet quality, token quality, and market density signals.
  • Instrumented the pipeline with Grafana, Loki, and Tempo for end-to-end observability — live throughput dashboards, structured log search, and distributed tracing.
Dec 2025 — May 2026
02
Algonox Technologies
Software Engineer · Hyderabad
  • Built automated email notification system for file queue transitions and failure alerts, improving SLA compliance.
  • Implemented complex business rules to clean and validate noisy data, boosting data extraction accuracy by 40%.
  • Designed automated KPI reporting system to track extraction accuracy and manual intervention rates.
  • Developed User Dormancy Management Module to manage user lifecycle states based on inactivity thresholds.
Sep 2024 — Dec 2025

Personal
Projects

01
RAG-based PDF Q&A System
Python · LangChain · ChromaDB · HuggingFace · Groq · Flask
  • Built an end-to-end Retrieval-Augmented Generation pipeline ingesting PDFs, chunking content, and generating vector embeddings via HuggingFace sentence-transformers indexed in ChromaDB for semantic retrieval.
  • Integrated Groq Cloud LLM API (llama-3.1-8b-instant) through LangChain LCEL pipelines — delivering sub-second context-grounded answers with source citations via a Flask REST API and browser chat UI.
  • Designed for modularity: switched from local Ollama to Groq with a single-line change, demonstrating provider-agnostic architecture for LLM applications.
GitHub ↗
02
weather-enquire — Weather CLI
Python · OpenWeather API · rich · Published to PyPI
  • Built and published a terminal weather tool to PyPI (pip install weather-enquire) — fetches current conditions and multi-day forecasts for any city worldwide.
  • Resolves cities via OpenWeather's Geocoding API (covering small towns the legacy endpoint misses) and renders colour-coded panels and tables with the rich library.
  • Added a 10-minute on-disk response cache, graceful error handling with distinct exit codes, and a clean src-layout package with a console-script entry point.
GitHub ↗
03
Flight Ticket Price Prediction
Python · scikit-learn · Random Forest · pandas · Flask
  • Built an end-to-end ML regression system predicting domestic Indian flight prices — feature-engineered date, time, duration and route data, and one-hot encoded categorical features into 29 model inputs.
  • Compared Linear Regression, Decision Tree and Random Forest; the tuned Random Forest was the best performer and is served through a Flask web app for live price predictions.
  • Published as a research paper — "Predicting Airline Ticket Prices Using Machine Learning," IJSREM Vol. 8 Issue 4 (April 2024).
GitHub ↗
04
Real-Time Order Updates
Python · Flask · PostgreSQL · Server-Sent Events
  • Built a backend service that pushes database changes to connected clients in real time — any insert, update, or delete on the orders table is instantly broadcast to all listeners without polling.
  • Used Server-Sent Events (SSE) for efficient one-way server-to-client push, backed by PostgreSQL and a thread-safe subscriber queue in Flask.
  • Includes a Python CLI client and a test script to demo the full flow — create, update, and delete orders with live terminal output.
GitHub ↗
Let's
Talk.
Email narasimharao2743@gmail.com ↗ LinkedIn View Profile ↗ GitHub narasimharao2743 ↗ Phone +91 63032 27485 ↗