Drive the future of personalized learning by architecting innovative agentic experiences. This pivotal role leverages AI, machine learning, and automation to create adaptive, embedded learning solutions that accelerate skill development and enhance learner outcomes. You will reimagine how individuals discover, build, and apply skills, creating intelligent systems that understand context and adapt to evolving needs.

Microsoft is dedicated to empowering every person and organization globally. We foster a growth mindset, encourage innovation, and collaborate to achieve shared goals. Our values of respect, integrity, and accountability cultivate an inclusive environment where everyone can thrive.

Define and execute a transformative strategy for AI, agentic systems, machine learning, data, and automation in Learning & Development. Lead programs from inception through implementation and optimization, managing dependencies, risks, and cross-functional delivery.

Implement advanced analytics (descriptive, diagnostic, predictive, prescriptive), including machine learning and agentic AI, to identify skill gaps, forecast needs, and measure impact. Develop Microsoft Fabric data pipelines, lakehouses, and Power BI reports for data-driven insights. Establish data quality controls and measurement frameworks for learning effectiveness.

Design and deploy agentic AI solutions, integrating Azure AI Foundry, Azure OpenAI, Azure AI Search, Microsoft Copilot, and Azure Machine Learning for personalized learning experiences. Implement RAG, grounding, and feedback mechanisms to enhance AI quality.

Utilize Azure AI Document Intelligence and Azure AI Speech to extract information from documents and integrate speech capabilities into learning solutions. Develop workflows to transform spoken interactions and documents into searchable knowledge.

Architect secure, scalable Azure solutions using services like Azure App Service, Azure Functions, and Azure Cosmos DB. Develop applications and APIs using Python and C#/.NET. Design data models and implement robust security practices.

Establish CI/CD pipelines with Azure DevOps for automated testing and deployment. Automate infrastructure provisioning using infrastructure as code and business workflows with Power Automate and Azure Logic Apps. Improve delivery efficiency through reusable components and automated processes.

Continuously iterate on program and solution design using real-time feedback, telemetry, and analytics. Monitor solution performance, reliability, and cost to ensure sustained value.

Translate technical insights into actionable recommendations for diverse audiences. Collaborate effectively with business leaders, subject-matter experts, and engineering teams. Foster a data-driven culture and shared accountability.

Champion responsible AI principles, including fairness, transparency, privacy, security, and accessibility. Establish robust evaluation, human oversight, and governance for AI solutions.

A Master's degree with 10+ years of experience in learning and development, technical roles, business development, or related fields, OR a Bachelor's degree with 12+ years of equivalent experience. Equivalent experience may substitute for a degree.

Demonstrated expertise in technical program management, learning and development, knowledge management, customer success, or a related technical discipline. Proven ability to lead cross-functional initiatives and translate business needs into technical solutions with measurable outcomes.

Technical proficiency includes hands-on experience with Microsoft Azure, Azure AI services (including Azure OpenAI, Azure AI Foundry), Azure AI Document Intelligence, Azure AI Speech, Azure App Service, Azure Cosmos DB, and Microsoft Fabric. Strong development skills in Python and C#/.NET are essential.

Experience with CI/CD practices using Azure DevOps, workflow automation tools like Power Automate and Azure Logic Apps, and a working knowledge of source control, automated testing, API integration, cloud security, and troubleshooting are required.

Excellent analytical, problem-solving, stakeholder management, and communication skills are crucial. The ability to explain complex technical concepts to non-technical stakeholders and influence decisions across organizational boundaries is essential.

Preferred qualifications include experience with Azure Machine Learning, MLOps, prompt engineering, AI evaluation practices, and cloud infrastructure provisioning tools such as Bicep or Terraform. Familiarity with enterprise data governance, privacy, accessibility, and security requirements is also advantageous. Relevant Microsoft certifications are a plus.