Summary
Sayantan Mukherjee is an AI software engineer with 10 years of experience building production-ready solutions that bridge large language models, knowledge graphs, and industrial data to drive asset optimization and compliance. Currently at parabole.ai, he designs explainable RAG pipelines and integrates generative outputs with ontologies and RDF stores (RDFox, GraphDB, AnzoGraphDB) to turn unstructured logs into actionable insights. His background spans enterprise SAP development, full-stack FinTech systems, IoT-to-cloud pipelines, and healthcare ML research, giving him a rare blend of symbolic reasoning and practical engineering. Comfortable with prompt engineering, fine-tuning, semantic vectorization and SPARQL-driven integrations, he focuses on making advanced AI auditable and operational. Based in New York with an MS in Computer Science from NYU, he combines academic grounding with hands-on delivery across cloud, embedded, and big-data environments.
10 years of coding experience
2 years of employment as a software developer
Secondary, Science, Secondary, Science at Garden High School - India
Bachelor of Technology, Computer Science and Engineering, Bachelor of Technology, Computer Science and Engineering at KIIT - Kalinga Institute of Industrial Technology
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at New York University
Higher Secondary, Mathematics and Computer Science, Higher Secondary, Mathematics and Computer Science at Delhi Public School, Ruby Park
English, Bengali, Hindi, Spanish, French