Retrieval-augmented generation (RAG) systems, Java, Python, designing and building AI applications, event-driven microservices, serverless compute, Go, applied foundation models, agentic workflows, cloud native architecture, containerized workloads, cloud-native application development

Pyspark, Kafka, Sql, Microservices, Rabbitmq, Hl7, Dicom, Python, Kubernetes, AWS, OneSpace, Infrastructure-as-code, CI/CD pipelines, NATS

Prometheus, Bash, Gcp, Docker, Terraform, Ansible, Python, Kubernetes, AWS, Cloud Logging, CI CD, GitHub Actions

Java, Data Transformation, Json, Rest Apis, Python, Google Cloud, Google Retail Search, Product catalog schema, Ingestion pipelines, Search API integration, Troubleshooting

bedrock , Json, Tool Calling, RAG Implementation, LangGraph ADK, Agentic Frameworks, Python Programming Language, GPT Model Usage Evaluation, Claude, Azure OpenAI, Pydantic Validation, Agent Memory Patterns, Azure AI Studio, Agentic RAG, Context Prompt Engineering, Gemini, Function Calling

code coverage , perl, Regression Testing, Ovm, Ethernet Protocols, Python, multiple RTL simulators, X-propagation, Uvm, systemverilog, functional coverage