PNSY Ramith

Software Engineer

Tamil Nadu, India5 yrs 9 mos experience

Highly StableAI ML Practitioner

Key Highlights

Engineered high-performance microservices handling millions of requests.
Developed AI-driven systems for predictive anomaly detection.
Optimized AWS services reducing latency and improving reliability.

Stackforce AI infers this person is a Backend-heavy Fullstack developer in the SaaS and Fintech industries.

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Skills

Core Skills

Spring BootMicroservicesSoftware DevelopmentAmazon Web Services (aws)

Other Skills

AI TestingAWSAWS LambdaAWS SDKApache KafkaAuroraC (Programming Language)C++CloudWatchData Structures and AlgorithmsDockerDynamoDBElasticsearchGitGrafana

Experience

Walmart

Software Engineer

Sep 2023 – Present · 2 yrs 6 mos

Designed and implemented high-performance microservices using Java 17, Spring Boot, and Spring Cloud Gateway, handling over 5 million API requests per day across distributed systems. Engineered an AI testing framework to validate LangChain-based connectors, automate LLM prompt testing, and perform response consistency scoring, achieving 85% AI reliability coverage.
Integrated Kafka Streams for asynchronous communication with at-least-once delivery semantics, improving system throughput by 60%. Developed and optimized AWS Lambda-based connectors using the AWS SDK, reducing cold start latency by 40%. Implemented distributed tracing pipelines using OpenTelemetry and CloudWatch for enhanced observability and debugging.

Java 17Spring BootSpring Cloud GatewayKafka StreamsAWS LambdaOpenTelemetry+2

Paypal

Software Engineer

Jun 2020 – Sep 2023 · 3 yrs 3 mos · Chennai

Designed and developed distributed microservices using Java 11, Spring Boot, Spring Cloud, and Kafka, processing over 10 million requests per day for dealer management systems. Built a DB Migration Service with Spring Batch and Redis, enabling high-throughput data synchronization between MySQL and DynamoDB with 65% faster performance. Designed secure, low-latency cross-cluster communication using JWT and OAuth2, optimizing service response time by 35%.
Deployed microservices on Docker and Kubernetes (EKS), monitored with Prometheus and Grafana, which improved system uptime by 40% and sustained over 1 million concurrent event loads, verified through JMeter and Gatling performance testing.
Engineered an AI-driven Alert Management System using Java 11, Spring Boot, Spring Cloud Gateway, Kafka Streams, and Elasticsearch to process and monitor 300K+ real-time events per day with predictive anomaly detection and intelligent alerting. Integrated an AI testing layer to validate inference accuracy and reliability using JUnit5, Mockito, and Testcontainers, achieving 90% automation coverage.

Java 11Spring BootSpring CloudKafkaSpring BatchRedis+8

Amazon

Technical Intern

Jan 2020 – Jun 2020 · 5 mos

Designed and developed high-performance microservices using Java 17, Spring Boot, and AWS services, handling millions of real-time transactions per day with low latency and 99.99% uptime. Implemented event-driven architectures using Kafka and SQS, optimized interactions with DynamoDB and Aurora, and automated CI/CD pipelines, reducing release times by 40%.
Engineered AI validation frameworks for recommendation engines, automating machine learning output verification and improving reliability by 30% across distributed systems. Built scalable, fault-tolerant distributed services using Spring Cloud and AWS, ensuring seamless operation under high load.

Java 17Spring BootAWSKafkaSQSDynamoDB+2