Kubernetes, python, Spark, Docker, seldon, kubeflow

agile environment , Scalability, Gen AI, Architectural Design, Efficiency, Extensibility, Large-scale distributed systems

Continuous Integration, Logging, Automated Testing, context-engineering strategies, data pipelines, tracing, production-quality systems, Monitoring, retrieval systems, observability systems, AI agents, agent infrastructure, ML systems, evaluation frameworks for AI systems

S3, Cloudformation, Dynamodb, Node.js, Sql, Typescript, Terraform, Docker, Distributed Systems, AWS, Infrastructure as Code, AWS CDK, AI fundamentals, AI safety governance, Serverless applications, EventBridge, Aurora

Java, Hadoop, Aws Services, Big Data Technologies, API design, Microservices, Docker, Terraform, Distributed Systems, Spark, Kubernetes, Python, data pipelines, agentic AI-enabled development practices, CI CD pipelines, data visualisation tools, data processing frameworks

IIOT, Pytest, Sql, Jenkins, Jmeter, Automation Frameworks, Azure DevOps, industrial software solutions, Playwright, CI CD integration, KQL, quality engineering, GitHub Actions, DataOps, OT IT adapters, testing strategies, IAM security, EDGE

Ml, Cloud Infrastructure, distributed databases, large-scale distributed systems, Ai, high-throughput APIs, real-time data processing, architectural strategy

Golang, Distributed Systems, Postgres, Python, data lakes, K8S

Android, Design Patterns, Kotlin, Multi-threading, Secure Enclave, Cross-platform concepts, security engineering, Performance optimization, AI coding assistants

Algorithms, Agile Development, MySQL, Azure Data Lake, data structures, Python, AWS, multithreading, Power Bi, Dynamodb, Azure Sql, Devops, Gcp, Synchronization, MongoDB, Azure, Kubernetes, microservice-based architecture, Go, cloud programming, HTTP applications, AI-powered applications, web services development, asynchronous patterns, CosmosDB