Program Management & Delivery
- Lead end-to-end delivery of Agentic AI projects from ideation and PoC to deployment and scaling across Microsoft platforms.
- Manage project scope timelines budgets and risks while ensuring alignment with business goals and technical feasibility
Microsoft AI Ecosystem Integration
- Coordinate the implementation of Microsoft-native AI components including Azure AI Foundry Power Automate and Copilot integrations.
- Ensure solutions are compliant with Microsofts Responsible AI principles including cost optimization bias detection and audit workflows
Stakeholder Engagement
- Act as the primary liaison between business stakeholders technical teams and Microsoft partners.
- Facilitate workshops demos and governance reviews to ensure stakeholder alignment and transparency
Agile Execution & Governance
- Apply Agile/Scrum methodologies to manage sprints backlogs and iterative delivery cycles.
- Track KPIs manage change requests and ensure documentation and audit readiness.
Innovation & Reusability
- Promote reuse of accelerators templates and frameworks across AI projects.
- Contribute to the development of delivery playbooks and best practices for Microsoft Agentic AI programs
Required Skills & Qualifications
- Bachelors / Masters degree in computer science Engineering Mathematics Statistics or related field
- Proven experience managing AI/ML or GenAI projects ideally within Microsoft environments.
- Strong understanding of Microsoft AI stack: Azure AI Power Platform Microsoft Copilot and Semantic Kernel.
- Familiarity with orchestration frameworks like LangChain LangGraph or AutoGen is a plus.
- Experience in managing deploying activities with Gen AI stack/services provided by various platforms such as AWS GCP Azure
- Experience in project management for AI/ML Generative AI and Agentic AI Projects.
- Excellent communication stakeholder management and cross-functional leadership skills.
- PMP PRINCE2 or Agile certifications preferred.
- Collaborate with data engineers data scientists and business stakeholders to understand the data and the business problems.