Systems that hold up at 3am.

Develop

I build the unglamorous machinery real products run on. Across 5.5+ years and 50+ production projects the pattern is usually the same: something slow, fragile or expensive comes in, and something fast, boring and cheap goes out.

What I build

• Low-latency microservices and APIs that hold under real traffic
• Data pipelines that survive production volume, not just the demo
• Real-time infrastructure on Redis and WebSocket
• GenAI systems with LLMs and RAG, shipped rather than prototyped

How I work

• Profile first, then optimise. Guessing is expensive
• Own it end to end: infrastructure, CI/CD, and the 3am page
• Test automation and code review as defaults, not afterthoughts
• The security work nobody volunteers for, including HIPAA and GDPR

Where I'm headed

• A hands-on tech lead role, owning architecture without leaving the code
• Teams that ship, measure, and fix what the numbers show
• More mentoring. It is the part I would keep above everything else

If that is the kind of engineer you are hiring, let's talk.

1. Feb 2022 → now

   4 yrs 8 mos

   

   Senior Software Engineer

   Elucidata · New Delhi (remote)

   • Rebuilt the graph engine from R to Python/Polars for 10× faster runtime, 80% less memory, scaled to 100K+ entities across 1,000+ pathways.
   • Optimised KEGG pathway rendering: runtime 22 minutes → under 1 minute, UI latency 15 minutes → under 1 second.
   • Built a production Streamlit + Python app with bi-directional S3↔EC2 sync and Elastic IP deployment, giving instant h5ad visualisation, runtime from hours to seconds.
   • Developed a React + Next.js + FastAPI platform for OMOP table mapping with PostgreSQL validation, cutting manual mapping effort by 70%.
   • Designed AWS Batch pipelines running 10,000+ jobs/month on a spot/on-demand mix, cutting infrastructure costs by 28%.
   • Architected a Redis + WebSocket microservice (EC2, VPC, CI/CD) delivering sub-100ms notifications at scale.
   • Built production Shiny apps and React/Node.js/Python POCs that powered client demos and secured new contracts.
   • Shipped production GenAI apps using LLMs, RAG and vector databases (FAISS / Qdrant) for real-time semantic search and summarisation on domain-specific data.
   • Developed 10+ interactive dashboards in R Shiny and React, including a Yale University data explorer later published in a peer-reviewed journal.
   • Diagnosed and fixed a major memory leak in tooltip rendering for 90% less memory and no more Shiny disconnects.
   • Mentored three engineers, introduced CI/CD automation (85% test coverage) and code review, cutting 40% fewer production issues.
   • Hardened infrastructure security: HIPAA/GDPR-compliant handling across S3, RDS and VPC, passing a third-party audit with zero critical findings.

   Python · Polars · FastAPI · React · Next.js · AWS Batch · Redis · WebSocket · R Shiny · LLMs / RAG

2. Jan 2021 → Feb 2022

   1 yr 2 mos

   

   Software Engineer

   Ignite Solutions · Pune (remote)

   • Built demand-forecasting pipelines (Python, Airflow) reducing MAPE by 15% for 500K retail energy meters.
   • Modelled 100M credit-card transactions, boosting upsell precision to 90% in the pilot region.
   • Created a Flask-based recruitment portal integrated with Google Workspace, cutting hiring cycle time by 30%.

   Python · Airflow · Flask · Forecasting

3. Aug 2019 → May 2020

   10 mos

   

   Software Engineer, Intern

   InterviewBit · Bengaluru, India

   • Implemented an end-to-end auto-suggestion tool measuring semantic similarity between student queries and existing solutions, deployed as a REST API on AWS EC2 with a Flask backend, reducing query resolution time for 72% of students from 2 days to 13.3 minutes on average. Built a KPI dashboard on top using SQL.
   • Built an NLP tool to calculate the percentage of code vs. text in TA responses, increasing overall student–TA interaction.
   • Wrote scripts to email and migrate 1,500+ students from Flock to the open-source platform Mattermost.
   • Revamped InterviewBit's web pages and created content for Data Science, Machine Learning and Deep Learning tracks.

   Python · NLP · Flask · AWS EC2 · SQL

4. Jun 2019 → Jul 2019

   2 mos

   

   Data Science, Intern

   upGrad · Remote

   • Mentored 200+ students, providing clear, positive, line-by-line actionable feedback on their submitted projects using upGrad's code review tool for data science courses.

   Python · Code review · Mentoring

5. Jun 2018 → Jul 2018

   2 mos

   

   Data Analyst, Intern

   MyGov (MoEIT, India) · New Delhi (remote)

   • Analysed public sentiment on government policies and campaigns across social media.
   • Exported over 4,000 tweets with the Twitter API and built a hybrid solution classifying each tweet as positive or negative with a KNN algorithm.
   • Performed data mining operations on websites for various internal purposes.

   Python · Twitter API · Sentiment analysis

6. Aug 2017 → Sep 2018

   1 yr 2 mos

   

   Lead Organizer

   Microsoft Student Technical Community, LPU · India

   • MSTC hosts community events guiding professionals across different technologies. It is a platform where like-minded people come together to share and learn about technology.
   • As a lead speaker, shared knowledge on front-end technologies.

   Community · Public speaking · Front-end