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Hi, I’m Prabhas, a software engineer focused on building scalable backend systems and event-driven microservices. I enjoy turning complex requirements into reliable, high-performance services using Java, Spring Boot, REST APIs, and Apache Kafka. I thrive in data-driven environments with cloud-native architectures (AWS), caching, asynchronous processing, and efficient data pipelines. I’m passionate about delivering maintainable, production-ready solutions and collaborating across teams to improve reliability, automation, and overall system efficiency.…Hi, I’m Prabhas, a software engineer focused on building scalable backend systems and event-driven microservices. I enjoy turning complex requirements into reliable, high-performance services using Java, Spring Boot, REST APIs, and Apache Kafka. I thrive in data-driven environments with cloud-native architectures (AWS), caching, asynchronous processing, and efficient data pipelines. I’m passionate about delivering maintainable, production-ready solutions and collaborating across teams to improve reliability, automation, and overall system efficiency.

Prabhas Juvvanapudi

Full Stack Developer, Back-End Developer, Web Developer, +2

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Hi, I’m Prabhas, a software engineer focused on building scalable backend systems and event-driven microservices. I enjoy turning complex requirements into reliable, high-performance services using Java, Spring Boot, REST APIs, and Apache Kafka. I thrive in data-driven environments with cloud-native architectures (AWS), caching, asynchronous processing, and efficient data pipelines. I’m passionate about delivering maintainable, production-ready solutions and collaborating across teams to improve reliability, automation, and overall system efficiency.…Hi, I’m Prabhas, a software engineer focused on building scalable backend systems and event-driven microservices. I enjoy turning complex requirements into reliable, high-performance services using Java, Spring Boot, REST APIs, and Apache Kafka. I thrive in data-driven environments with cloud-native architectures (AWS), caching, asynchronous processing, and efficient data pipelines. I’m passionate about delivering maintainable, production-ready solutions and collaborating across teams to improve reliability, automation, and overall system efficiency.

Available to hire

Hi, I’m Prabhas, a software engineer focused on building scalable backend systems and event-driven microservices. I enjoy turning complex requirements into reliable, high-performance services using Java, Spring Boot, REST APIs, and Apache Kafka.

I thrive in data-driven environments with cloud-native architectures (AWS), caching, asynchronous processing, and efficient data pipelines. I’m passionate about delivering maintainable, production-ready solutions and collaborating across teams to improve reliability, automation, and overall system efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Software Engineer at ServiceNow

November 1, 2024 - Present

Designed and engineered event-driven microservices using Java, Spring Boot, Spring MVC, and Apache Kafka to ingest alerts from enterprise monitoring systems and generate ITSM incidents via REST APIs, processing 2M+ events/month and reducing manual ticket creation delays by 45%. Built backend services to automate incident classification, prioritization, and routing, cutting manual triage effort by 40% and improving workflow efficiency across high-volume support systems. Implemented RESTful APIs with ServiceNow ITSM, Prometheus, Datadog, and internal systems for real-time event correlation and faster detect-to-resolve workflows. Optimized performance with asynchronous processing, Redis caching, SQL query tuning, and indexing to improve throughput and latency. Developed data pipelines and analytics using Python, SQL, and Snowflake to track MTTR, SLA compliance, and automation success rates.

Software Engineer – Machine Learning at Infinite Infolab

August 1, 2020 - July 1, 2023

Designed and deployed ML models using Python, Scikit-learn, and XGBoost for customer behavior prediction and anomaly detection, improving prediction accuracy by 30% and enabling data-driven decision-making. Built scalable ETL pipelines using Python, SQL, and Pandas to process multi-million-record datasets, improving data availability and reducing preparation time for analytics and modeling. Engineered feature pipelines, data preprocessing, and transformation to enhance model performance and stability. Integrated ML models into backend systems via Flask-based REST APIs for real-time inference and seamless consumption by internal applications. Optimized training workflows with parallel processing and efficient data handling techniques, collaborating with cross-functional teams to translate business requirements into data science solutions.