Kumar Nitesh

I am a Staff-level engineer with over 12 years of experience architecting scalable, high-performance enterprise web applications and leading Generative AI solutions using Java, J2EE, Python, and RDBMS technologies.

I design data flow architectures for Gen AI systems, leveraging LLMs, Knowledge Graphs, Abstract Syntax Trees (AST), and observability tools. At Tesco I contributed to a COBOL modernization pipeline that used AST generation, Knowledge Graphs, embeddings in Qdrant, Azure Open AI for context-aware Q&A, and integrated LLM evaluations and monitoring for reliability.

I drive cloud-native transformations and microservice adoption to improve resiliency and delivery velocity—one project accelerated feature delivery by 30%. I have architected notification and storage services using Couchbase, Cloudian, Docker, and Kubernetes/AKS and optimized critical processing with up to 80% performance gains in key modules.

I mentor cross-functional teams, establish best practices in system design, DevOps, and LLM evaluation, and have authored a book and contributed patents. I seek opportunities to lead engineering teams building production-grade generative AI and cloud-native systems that deliver measurable business impact.