Summary
Eswar Lakshminarayanan is a software engineer with 8 years of experience building scalable, serverless backend systems and data-driven features for large-scale cloud platforms. Currently at AWS, he architected a globally replicated Learner State Service and led the public launch of the AWS Skills Profile, demonstrating strength in multi-region DynamoDB modeling, event-driven architectures, and GraphQL BFF integrations. Previously at Amazon he designed transactional single-table DynamoDB patterns and event propagation pipelines to automate financial reconciliation at enterprise scale. He pairs a practical production focus—observability, idempotency, secure-by-default infrastructure, and CI/CD testing—with a strong academic foundation (M.S. in Data Informatics, USC) and earlier ML/NLP work that produced >90% precision in entity extraction. Eswar moves fluidly between backend systems, data engineering, and ML-informed solutions, and has a track record of shipping resilient, auditable systems that reduce operational toil. Based in Los Angeles, he favors designs that balance low-latency global availability with pragmatic fault isolation.
8 years of coding experience
7 years of employment as a software developer
M.S in Data Informatics (Machine Learning Data Mining Data Visualization), M.S in Data Informatics (Machine Learning Data Mining Data Visualization) at University of Southern California
Certificate Program in Big Data Analytics and Optimization Machine Learning, Certificate Program in Big Data Analytics and Optimization Machine Learning at International School of Engineering (INSOFE)
Deep Learning Nanodegree, Deep Learning Nanodegree at Udacity
Engineer’s Degree Information Technology, Engineer’s Degree Information Technology at Anna University Chennai
English, Tamil, Telugu