Headline

Software Engineer I @ Toast | Backend & Distributed Systems | Java • Kotlin • TypeScript • gRPC • GraphQL • Apache Pulsar • AWS • Splunk

About

I am a Full Stack Software Engineer at Toast, where I design, build, and scale the distributed systems that power 170,000+ restaurants globally. My expertise lies in developing highly available, low-latency microservices using Java and Kotlin, optimizing data persistence with DynamoDB, and building efficient APIs via gRPC and GraphQL. Because operating at scale requires absolute reliability, I focus heavily on: • Event-Driven Architecture: Utilizing Apache Pulsar and RabbitMQ for robust, asynchronous message streaming. • Production Observability: Leveraging DataDog and Splunk for real-time monitoring, log analysis, and performance tuning. • Safe Deployments: Executing complex, feature-flag-driven rollouts to ensure zero downtime. I am deeply passionate about distributed systems, performance engineering, and system design. I love solving complex infrastructure puzzles and contributing to open-source projects. Core Technical Stack: Languages: Java, Kotlin, TypeScript, Python Frameworks & Protocols: gRPC, GraphQL, Dropwizard, Spring Boot Cloud & Databases: AWS (Amazon Web Services), DynamoDB Messaging & Observability: Apache Pulsar, RabbitMQ, DataDog, Splunk, Git

Location

Bangalore Urban

AI stack

claude code

codex

Work experience

Software Engineer - I at Toast, Aug 2025 - Present · 1 yr 2 mos, Bengaluru, Karnataka, India · Hybrid, • Team: Enterprise Away Team, focused on building and shipping new features for Toast's large enterprise customer segment, supporting 40,000+ of the 170,000+ global restaurants on the platform. • Writing and maintaining high-throughput internal microservices using Java, Kotlin, gRPC, and GraphQL to optimize service-to-service communication. • Debugging complex distributed microservice connections and asynchronous messaging pipelines powered by Apache Pulsar and RabbitMQ, using Splunk and DataDog to identify bottlenecks and trace logs. • Designing and scaling resilient data models in Amazon DynamoDB to maintain low-latency read and write performance during peak restaurant traffic periods. • Collaborating on backend feature rollouts through continuous integration pipelines and feature-flag strategies to minimize deployment risk for enterprise customers.

Software Engineer Intern at Toast, May 2025 - Aug 2025 · 4 mos, Bengaluru, Karnataka, India · Hybrid, • Team: Data Science Team, worked on fraud detection model pipelines and learned how machine learning models are integrated into backend microservices for real-time transaction scoring. • Built, tested, and deployed backend services in AWS-hosted pre-production environments using Java and Dropwizard. • Worked with data engineering pipelines leveraging Amazon S3 and Snowflake to support fraud model training, validation, and data processing workflows. • Collaborated with data scientists and backend engineers to integrate, test, and operationalize fraud detection models within production-ready systems.

Research Intern at National Institute of Technology Tiruchirappalli (NIT Trichy), May 2023 - Jul 2023 · 3 mos, Remote, • Developed and optimized customized Deep Learning models for legal text classification, improving classification accuracy and processing efficiency on complex legal documents. • Integrated Explainable AI (XAI) frameworks (such as SHAP/LIME) to demystify black-box neural networks, providing interpretable visual insights into model decision-making processes for legal stakeholders. • Engineered NLP preprocessing pipelines using Python to handle unstructured, domain-specific legal terminology, significantly reducing noise and enhancing feature extraction.

Education

Bachelor of Technology - BTech, Computer Science and Engineering, Birla Institute of Technology, Mesra

PCM, Sri Chaitanya College of Education