Looking for a job

Alapan Bagchi

@alapanbagchi

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I build scalable backend systems, AI applications, and cloud infrastructure for fast-moving products.

Ireland

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What I'm looking for

I'm looking for software engineering opportunities in tech companies where I can work in a structured environment, build scalable products, and grow as a developer.

At Algorithmics Westmeath, I build PeanutSave's Golang backend and React Native client app, including an immutable double-entry ledger, a BERT transaction classifier, and secure RBAC-enabled RAG for interbank financial data.

Previously at Querkauf UG, I architected event-driven Python, Kafka, and Redis pipelines and delivered enterprise features for a B2B marketing automation suite. I reduced high-traffic data-load latency by 95%, from 60 seconds to 500 milliseconds, by resolving N+1 queries and introducing covering indexes.

I've also built an AI power forecasting platform processing more than 20 million telemetry records and a LeetCode-style university platform serving 10,000+ students during concurrent coding contests. I enjoy owning projects from concept through deployment while working closely with founders, CTOs, and cross-functional teams.

Experience

Work history, roles, and key accomplishments

Current

Full Stack AI Software Engineer

Current

Algorithmics Westmeath

Oct 2024 - Present (1 year 11 months)

Built backend with Golang and client-facing app with React Native for PeanutSave, a gamified finance app. Engineered immutable double-entry ledger, fine-tuned BERT classifier, developed RBAC-enabled RAG system, and optimized PostgreSQL data layer.

React Native PostgreSQL Kafka Docker AWS BERT RAG RBAC CI CD Nginx Cloudflare

Education

Degrees, certifications, and relevant coursework

Technological University of Shannon

Master of Science, Software Design with Artificial Intelligence

2024 - 2025

Grade: First Class Honours

Pursuing a Master's in Software Design with Artificial Intelligence, achieving First Class Honours. Thesis focused on predictive modeling of national electrical energy consumption using meteorological and economic data.