We are seeking an experienced AI TDM (Technical Develivery manager) with strong expertise in Agile delivery, Release Management, and AI-driven project execution. The ideal candidate will combine traditional project management excellence with a deep understanding of AI concepts such as Agentic AI and Prompt Engineering, ensuring efficient and intelligent delivery of enterprise solutions. This role requires hands-on experience with JIRA, Confluence, and Agile frameworks, along with the ability to integrate AI capabilities into delivery lifecycle management to improve efficiency, predictability, and scalability. Key Responsibilities AI-Driven Project & Delivery Management Lead end-to-end delivery of AI-enabled products and enterprise applications. Incorporate AI techniques (e.g., Agentic AI systems, prompt engineering) into project workflows and delivery pipelines. Identify opportunities to leverage AI for automation, decision-making, and predictive insights in delivery management. Drive adoption of AI tools for planning, risk identification, and resource optimization. Agile Program & Release Management Manage Agile ceremonies (Sprint Planning, Daily Stand-ups, Retrospectives, PI Planning). Own release planning, execution, and governance across multiple teams. Ensure alignment between business goals, technology roadmap, and release cycles. Implement Agile Release Train (ART) concepts and manage dependencies across teams. Track and optimize velocity, burn-down, release readiness, and quality metrics. Tools & Collaboration Act as a JIRA and Confluence champion, ensuring effective usage for Backlog management Sprint tracking Documentation and knowledge sharing Develop and maintain dashboards, reports, and workflows to improve transparency. Drive cross-functional collaboration across engineering, product, and stakeholders. Process Improvement & Governance Introduce AI-powered improvements in Release forecasting Risk mitigation Defect prediction Define and enforce best practices in Agile delivery and release management. Ensure compliance with enterprise governance and quality standards. Stakeholder Management Communicate effectively with senior leadership, product owners, and engineering teams. Provide data-driven insights and status updates using AI-enhanced reporting. Manage expectations, risks, and escalations proactively.