Teams at Egnyte

Fine-tune and optimize small language models using Hugging Face, TRL, and adapter methods. Build MLOps pipelines, deploy models to edge and mobile environments, meet strict latency targets, and monitor production accuracy, latency, and hardware utilization. Evaluate model quality through benchmarking and custom evaluation suites while applying quantization, pruning, and knowledge distillation.

Own the architecture and technical direction of large-scale distributed applications. Build secure, scalable Python backend services, contribute to Java services, guide platform strategy, mentor engineers, and establish engineering standards. Improve reliability, observability, automation, developer experience, security, testing, and operational excellence. Use AI-assisted development tools responsibly to increase productivity while maintaining software quality. Collaborate cross-functionally and lead through technical excellence, pragmatic architecture, and strong ownership.

Lead the Monetization Infrastructure engineering team, provide hands-on technical leadership, ensure high uptime and incident management, collaborate with Finance and Product, drive operational excellence, and champion adoption of AI-assisted SDLC practices.