system::identity — Kolkata, India

Anirban Bhattacharya

Back-end & AI systems engineer — building RAG pipelines and LLM-integrated services on top of Node.js and Spring Boot microservices, deployed and scaled with cloud and DevOps practices.

1,000+
API endpoints shipped
40%
Faster deployments
150ms
Latency shaved off
3+ yrs
Back-end experience
// request flow — RAG-augmented API
Client request API Gateway Node.js / NestJS Microservice Spring Boot Retrieval MySQL / Mongo LLM API RAG context Response grounded answer
// system architecture — REST API across microservices
Client REST call API Gateway routing / auth Auth Service Spring Boot User Service Node.js Order Service Spring Boot Database PostgreSQL / Redis

About

01

Over three years of back-end engineering experience with a growing specialization in applied AI — designing and shipping LLM-powered features, RAG chatbots, and intelligent recommendation systems integrated into production Node.js and Java Spring Boot platforms.

Built and integrated retrieval-augmented generation pipelines and LLM APIs to power conversational search, chatbots, and recommendation engines, improving search relevance and user engagement in enterprise applications.

Designs microservices and RESTful APIs backed by MySQL, PostgreSQL, MongoDB, and Redis, using AWS, GCP, Docker, and Kubernetes to keep delivery secure, automated, and highly available.

Cloud Architecture Microservices Design API Security Performance Optimization AI / LLM Integration System Reliability Engineering

Experience

02
SDE-II — Brainberg
09/2025 — Current active
  • Designed and integrated AI-powered RAG chatbots and recommendation engines using LLM APIs, improving search relevance and conversational experience across core products.
  • Built retrieval pipelines connecting internal MySQL and MongoDB data stores to LLM APIs for context-aware, data-grounded responses.
  • Architected 1,000+ RESTful API endpoints across Node.js, Express.js, NestJS, Java, and Spring Boot.
  • Engineered 10+ microservices spanning MySQL, PostgreSQL, MongoDB, and Redis alongside RabbitMQ and Kafka.
  • Automated CI/CD on AWS, cutting deployment time by 40% and accelerating release cycles.
  • Hardened security with JWT auth, caching, and RBAC — cutting API response time by 30%.
SDE-I — Marstrack Technologies
03/2023 — 09/2025 Bangalore, India
  • Prototyped early LLM API integrations and AI-assisted features, laying groundwork for later RAG and chatbot development.
  • Developed 1,000+ RESTful endpoints backed by MySQL and MongoDB, cutting average response time by 150ms.
  • Designed OAuth 2.0 / JWT / RBAC authentication services, improving login performance by 40%.
  • Optimized services with Redis, RabbitMQ, and Kafka, reducing request latency by 35%.
  • Managed 20+ deployments across AWS and Azure using Docker, Kubernetes, and Jenkins — cutting infra costs by 30%.
  • Led a team of 5 back-end and DevOps engineers serving 500+ daily active users.

Stack

03
Back-end & Languages
Node.jsExpress.jsNestJS Spring BootJavaTypeScript JavaScriptPython
AI & LLMs
RAG PipelinesLLM APIsPrompt Engineering Vector / Context RetrievalAI Integrations
Data
MySQLPostgreSQLMongoDBRedis
Cloud, DevOps & Messaging
AWSGCPDockerKubernetes CI/CDRabbitMQKafka

Project

04
Driver Management Application
Cloud-native platform built with React.js, Node.js, and MS SQL Server, deployed to Microsoft Azure through an automated GitHub Actions CI/CD workflow.
99.9%
Uptime

Education

05
B.E. in Computer Science and Engineering
AMC Engineering College, Bangalore, India
2023
Languages
English Hindi Bengali