Java, PostgreSQL, Scala, Spring Boot, Kafka, Emr, JIRA, Jenkins, Git, Docker, Reactjs, Spark, Apache Camel, MongoDB, Couchbase, Kubernetes, AWS, DocumentDB, Automated deployment, EKS, Harness, CI/CD pipelines

Paas, Hipaa, Artifactory, Iso27001, Agile, Python, AWS, Java, Saas, Iaas, Bash, Jira, Jenkins, Git, Perl, Kubernetes, Go, Blameless Postmortems, Service Level Objectives, Error Budgets, Kanban, Observability, Monitoring, Incident Response Process, PCI-DSS, Toil Management, Capacity Planning, SOCII

Power Bi, PowerShell, Sql, Machine Learning, Python, Windbg, KQL, ETW, AI-assisted analysis, Kusto, Windows Performance Analyzer, Azure services

Microservices, Reactjs, Distributed Systems, Knowledge systems, Performance and scalability optimization, Prompt engineering, DevOps practices, Retrieval-based systems, Agent assist automation, RAG, CI/CD, Java Spring Boot, LLM-based applications

Machine Learning, Apis, Deep Learning, Kubernetes, Distributed Systems, Microservices, Ai, reinforcement learning, Llm, Platform Scalability, AI Agents, Platform Governance, Production-grade AI Inference Pipelines, Platform Reliability, Agentic AI, DevOps Practices, Cloud-native Platforms, Streaming Systems, LLM Orchestration, AI-native Developer Experiences, Knowledge Graphs, Observability

graph databases , Sparql, Git, Rdf, Neo4j, Python, Graph RAG, AWS Bedrock, owl, SHACL, rdfs, Cypher, semantic technologies, RAG, Amazon Neptune, Knowledge Graphs, vector indexing, data-quality controls, embeddings, relationship extraction, chunking, document parsing, hybrid retrieval, entity extraction, ontologies, metadata extraction, observability

Distributed Systems, Data Architecture, Software development best practices, Data engineering best practices, Big data platforms, Data pipelines, Data Product Lifecycle Standards and Practices

Distributed Systems, Data Architecture, Data pipelines, Data Product Lifecycle Standards and Practices, Big data platforms, Data engineering best practices, Software development best practices