Program & Delivery Ownership:
- Own end-to-end delivery for AI/automation projects assigned to the AI CoE team from backlog intake through pilot and production rollout.
- Drive sprint planning, backlog refinement, and milestone tracking in Azure DevOps (ADO).
- Maintain visibility into task status, risks, and dependencies across the offshore development team.
- Ensure delivery adherence to AI CoE governance, security, and compliance standards.
Technical & Product Translation:
- Translate business requirements (captured via intake and AI CoE validation) into technical scope, user stories, and acceptance criteria.
- Partner with data scientists, engineers, and SMEs to define architecture, data sources, and integration needs.
- Review functional and technical designs to ensure they align with AI CoE standards and client needs. Stakeholder & Communication Management
- Serve as the day-to-day liaison between U.S. AI CoE, Steering Committee, and IDC teams.
- Communicate progress, risks, and blockers through dashboards and structured updates.
- Foster trust and transparency with practice leads and client-facing delivery teams.
Process & Quality Governance:
- Ensure every initiative follows the standard AI CoE process (Intake > Prioritization > Pilot > Scale > Monitoring).
- Maintain documentation, including Business Requirement Summaries, Technical Design Docs, and Pilot Reports.
- Conduct quality checks on backlog readiness, sprint output, and release deliverables.
People & Collaboration:
- Coordinate cross-functional collaboration between developers, data engineers, ML engineers, and QA.
- Support onboarding and knowledge sharing as new team members join the AI CoE team.
- Drive a culture of accountability, continuous improvement, and delivery excellence.
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