Kunal Babbar

Software Engineer

New Delhi, Delhi, India4 yrs experience

Most Likely To SwitchAI Enabled

Key Highlights

Reduced fraud cases by 50% with AI-driven solutions.
Migrated SQS to Kafka, enhancing system scalability.
Expert in building high-performance backend systems.

Stackforce AI infers this person is a Backend Engineer specializing in Fintech and AI/ML solutions.

Contact

Skills

Core Skills

JavaMicroservicesDatabasesArtificial Intelligence (ai)Aws

Other Skills

AWS LambdaAWS S3Amazon Web Services (AWS)Android DevelopmentAndroid JetpackApache KafkaCommunicationComputer ProgrammingComputer VisionData ScienceData StructuresDatabase Management System (DBMS)Docker ProductsEducationGoogle AppSearch

About

Hi, I’m Kunal – a backend engineer with 3+ years of experience building scalable, high-performance systems using Java, Spring Boot, Kafka, AWS, and microservices architecture. At Samsung, I contributed to multiple large-scale projects, including an LLM-powered fraud detection system that reduced fraud cases by 50%, a unified communication database integrating call, SMS, and WhatsApp data for real-time syncing, and semantic search optimization in messaging using AppSearch. Previously at PharmEasy, I worked in the logistics domain, where I migrated SQS queues to Kafka for 10+ services, built scalable microservices, and developed APIs for high-volume data processing, improving system scalability and efficiency. I specialize in distributed systems, cloud-native architectures, and high-throughput backend services, with a strong focus on latency, scalability, and reliability. Beyond backend engineering, I’m deeply interested in AI/ML-powered systems and how they can be applied to create intelligent, adaptive solutions. Outside of work, I enjoy exploring new technologies, traveling to new places, and engaging in problem-solving challenges that push my creativity.

Experience

Samsung electronics

Software Engineer

Feb 2023 – Present · 3 yrs 1 mo · Noida, Uttar Pradesh, India · On-site

Worked on a microservice architecture for Backend fraud detection engine using Qwen LLM and Unified Communication DB,Kafka and AWS Lambda; achieved 90%+ precision, cutting fraud cases by 50%.
Designed and implemented a consolidated backend database integrating Call, SMS, and WhatsApp data, reducing lookup time by 70% and enabling real-time syncing.
Deployed an SVM-based contact suggestion model with on-device inference, supported by backend APIs,MongoDB feature storage, and Kafka retraining pipeline; improved prediction accuracy to 92%, boosting engagement by 58%.
Developed and integrated on-device semantic search using Google AppSearch, improving search relevance by 75% and reducing query latency by 40ms.

SpringBootJavaApache KafkaRedisDatabasesMongoDB+2

Pharmeasy

2 roles

Software Engineer

Jul 2022 – Jan 2023 · 6 mos

Worked on microservice architecture with SpringBoot for scalable backend development in Logistics Department
Migrated SQS queues to Kafka for 10+ services which resulted in a 20% cost reduction
Migration to Kafka made the system highly scalable for large workloads that need to send messages in batches
Developed an API to automatically refresh the AWS S3 URL which contains proof of delivery uploaded by sprinters
Developed a sentry project for alerts and logging of production issues

Computer ProgrammingMicroservicesSpringBootKotlinKafkaSQS+15

Engineering Intern

Jan 2022 – Jun 2022 · 5 mos

Worked as a backend developer in Supply Chain Management Department
Migrated the Bulk Uploads to a new microservice which increased the efficiency of file upload by 30%

Computer ProgrammingMicroservicesSpring BootREST APIsKotlinMySQL+12