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Software Engineer with 6+ years of experience building scalable backend systems and intelligent applications across fintech, SaaS, and e-commerce. Strong expertise in Java, Python, Spring Boot, Node.js, and microservices architecture, along with distributed systems and Kafka-based event streaming. Experience deploying cloud-native solutions on AWS with Docker, Kubernetes, and CI/CD to ensure high availability and performance. Hands-on with AI/ML and LLM-based solutions (RAG, LangChain, OpenAI APIs), plus strong focus on observability, security, and building reliable, secure APIs and services in regulated environments.…Software Engineer with 6+ years of experience building scalable backend systems and intelligent applications across fintech, SaaS, and e-commerce. Strong expertise in Java, Python, Spring Boot, Node.js, and microservices architecture, along with distributed systems and Kafka-based event streaming. Experience deploying cloud-native solutions on AWS with Docker, Kubernetes, and CI/CD to ensure high availability and performance. Hands-on with AI/ML and LLM-based solutions (RAG, LangChain, OpenAI APIs), plus strong focus on observability, security, and building reliable, secure APIs and services in regulated environments.

Chaitanya Undi

Software Engineer, AI Engineer, Back-End Developer, +4

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Software Engineer with 6+ years of experience building scalable backend systems and intelligent applications across fintech, SaaS, and e-commerce. Strong expertise in Java, Python, Spring Boot, Node.js, and microservices architecture, along with distributed systems and Kafka-based event streaming. Experience deploying cloud-native solutions on AWS with Docker, Kubernetes, and CI/CD to ensure high availability and performance. Hands-on with AI/ML and LLM-based solutions (RAG, LangChain, OpenAI APIs), plus strong focus on observability, security, and building reliable, secure APIs and services in regulated environments.…Software Engineer with 6+ years of experience building scalable backend systems and intelligent applications across fintech, SaaS, and e-commerce. Strong expertise in Java, Python, Spring Boot, Node.js, and microservices architecture, along with distributed systems and Kafka-based event streaming. Experience deploying cloud-native solutions on AWS with Docker, Kubernetes, and CI/CD to ensure high availability and performance. Hands-on with AI/ML and LLM-based solutions (RAG, LangChain, OpenAI APIs), plus strong focus on observability, security, and building reliable, secure APIs and services in regulated environments.

Available to hire

Software Engineer with 6+ years of experience building scalable backend systems and intelligent applications across fintech, SaaS, and e-commerce. Strong expertise in Java, Python, Spring Boot, Node.js, and microservices architecture, along with distributed systems and Kafka-based event streaming.

Experience deploying cloud-native solutions on AWS with Docker, Kubernetes, and CI/CD to ensure high availability and performance. Hands-on with AI/ML and LLM-based solutions (RAG, LangChain, OpenAI APIs), plus strong focus on observability, security, and building reliable, secure APIs and services in regulated environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Intermediate

Javanese

Advanced

Work Experience

AI Software Engineer at US Bank

June 1, 2025 - Present

Architected scalable microservices using Java, Spring Boot and Python to power real-time transaction processing and fraud detection, improving throughput by 35% and enabling faster risk decisions. Engineered distributed data pipelines leveraging Kafka, AWS Lambda and S3 to process streaming financial events and support near real-time analytics, reducing data latency by 40%. Developed RAG-based LLM systems using LangChain and OpenAI APIs to enhance internal knowledge retrieval and customer query resolution, improving support efficiency and reducing manual lookup effort. Containerized and orchestrated services using Docker and Kubernetes (EKS) to ensure high availability and scalability, achieving 90% uptime for customer-facing applications. Implemented CI/CD pipelines with Jenkins and GitHub Actions to automate build, testing, and deployment workflows, reducing release cycle time and improving reliability. Optimized observability with CloudWatch, ELK Stack and Prometheus, reducing MTTR

AI Software Engineer at Avrhil IT Services

January 1, 2021 - November 1, 2023

Developed scalable backend systems using Python, Node.js and Express to support enterprise SaaS platforms, improving API response time. Built and optimized ETL pipelines using Python and SQL to ingest and transform large datasets for analytics. Designed RESTful APIs and microservices architecture to improve maintainability and reduce development effort. Designed and optimized NoSQL data models using MongoDB for high-volume event-driven applications, improving scalability and reducing query latency. Implemented asynchronous messaging systems using Kafka to handle high-volume workflows reliably. Deployed cloud-native applications on AWS (EC2, S3, RDS) and integrated React.js interfaces for dynamic experiences. Automated build and deployment pipelines using Jenkins and Docker and collaborated with QA/product teams to resolve production issues.

Software Developer at Flipkart

June 1, 2018 - December 1, 2020

Engineered high-performance backend services using Java and Spring Boot for e-commerce order processing under peak sale traffic. Developed C++ modules to optimize search and recommendation systems, improving response time and product discovery. Built event-driven workflows and optimized data storage across relational and NoSQL databases for distributed scalability. Created scalable REST APIs integrating with Angular/JavaScript frontend. Optimized MySQL queries for large-scale transactional systems and implemented Redis caching to reduce database load during high concurrency. Monitored performance and resolved production issues; contributed to code quality through best practices and code reviews.