Software Engineer at JPMorgan Chase & Co.
I'm a backend & infrastructure engineer at JPMorgan Chase & Co. I move workloads onto event-driven AWS platforms, modernize the Java services that critical workflows depend on, and build internal tools that make production easier to understand.
Bored? I built 10 tiny games. Play oneIngestion on AWS Glue, Airflow, Kafka, EventBridge and Lambda, landing data in Apache Iceberg.
Java and Spring services built to stay up, released safely with blue/green deploys and CI/CD.
MCP servers, RAG pipelines and semantic search that put LLMs to work on real operational data.
What I've built and how I built it.
Led the move of on-premises workloads onto a cloud-native, event-driven ingestion platform. Jobs that ran on on-prem VSIs now run as AWS Glue jobs orchestrated by Airflow, with Kafka carrying events between stages. Processing scales with the data, and compute costs dropped sharply.
Built an internal Model Context Protocol server that exposes real-time infrastructure and operational data. Engineers and stakeholders can query live system state directly, so production questions that took digging now get answered quickly.
Migrated a high-volume Query Service from legacy components to Spring MVC, one piece at a time, while the 300+ workflows depending on it kept running. Tech debt went down and uptime held at 99.9%.
Designed pipelines where a new S3 file emits an EventBridge event and a Lambda starts the matching Airflow workflow. The workflow loads multi-GB raw files into Iceberg tables in under two minutes, thanks to partition pruning and Parquet vectorized reads.
Built a blue/green deployment framework with validation checks before traffic switches over, wired into CI/CD. Releases go out with near-zero downtime and a clean path back if something looks wrong.
Automated certificate lifecycle management with Lambda and AWS Secrets Manager. Renewals across production services no longer need anyone to do them by hand.
Built features across Java, Spring Boot and React with a focus on performance. The module's throughput improved by about a quarter.
Led the migration of several applications to Java 17 and upgraded their Maven dependencies for security, compatibility and long-term maintainability.
Worked through critical findings from Raven and Fortify scans and fixed them. Expanded the JUnit/Mockito suites so the fixes stayed fixed.
Reworked the team's CI/CD pipelines to cut integration wait times, so the team could release more often.
Applied AI systems: retrieval, ranking and LLMs on real-world documents.
An AI-assisted review platform for legal and compliance teams. It reads contracts and regulatory documents, finds the clauses that matter, and checks them for compliance issues and risk.
A research agent that brings market data, earnings reports, regulatory filings and financial news into one interface for investment analysis.
The same résumé as a CLI. Type help to start.
What I reach for, grouped by layer.
Punjab Engineering College · Minor specialization in Mathematics
Coursework: Artificial Intelligence, Machine Learning, Operating Systems, Networks
When I'm not building pipelines, I'm piping buttercream. Here are a few cakes I've made, mostly buttercream roses, plus some chocolate lattice and ombré.
I'm glad to talk about backend, infrastructure, data platforms or applied AI. I reply fastest by email.