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Microsoft Corporation is an American multinational corporation headquartered in Redmond, Washington, that develops, manufactures, licenses, supports and sells computer software, consumer electronics and personal computers and services.
Position your GenAIOps skills for target roles through a career narrative, portfolio building, LinkedIn and GitHub optimization, and technical interview preparation.
Uses generative AI as an adversarial critic and pre-mortem partner to stress-test multi-agent architectures, uncover blind spots, and strengthen production-readiness.
Automate UI tests with Playwright, validate backend data with SQL queries, load-test with Apache JMeter, and use Generative AI to spot defect hot-spots and write status updates.
Execute a full QA cycle on a mock app: author Zephyr test cases in Jira, isolate API failures in Postman, automate checkout with Playwright, and generate Copilot reports.
Learn data engineering in Microsoft Fabric: work with Lakehouses and Delta format, ingest data with Dataflow Gen2, transform records, and join multiple sources into analytics-ready tables.
Translate QA lab projects into ATS-friendly resume bullets, curate a GitHub automation portfolio, and answer behavioral and technical interview questions with the STAR method in AI-powered mock interviews.
Learn to run smoke, regression, exploratory, usability and cross-browser tests, then document, triage and track defects in Jira Cloud using severity, priority and MTTR metrics.
Keep production data systems running in Microsoft Fabric: optimize pipeline performance, manage platform capacity, apply role-based access and data classification, and enforce data lifecycle policies.
Orchestrate multi-step data workflows in Microsoft Fabric: schedule pipelines with event triggers, design streaming architectures for telemetry, and monitor run histories to troubleshoot failures.
Prepare analytics-ready datasets in Microsoft Fabric: model fact and dimension tables, query Lakehouse and Warehouse data with SQL, and use AI assistants for transformation logic.
Design risk-based test strategies: author test cases in Jira with Zephyr, generate synthetic data with AI, calculate defect density, and build Excel metric dashboards.
Build healthcare AI agents with Azure AI Foundry, orchestrate multi-step workflows using Azure Functions and Logic Apps, and add RAG, contextual memory, and production testing.
Design and orchestrate collaborative multi-agent systems with AutoGen: group chat patterns, task delegation, Azure Entra ID security, SharePoint integration, and containerized Docker deployment with monitoring.
Build production-ready AI agents by integrating Azure OpenAI and GPT-4, developing Python bots with Bot Framework, orchestrating plugins with Semantic Kernel, and connecting through Microsoft Graph API.
Build data-driven ASP.NET Core applications: wire up dependency injection, custom middleware, global error handling, Entity Framework Core data models, and minimal APIs for a task management service.
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