EXL—Senior Manager

Job description

Description: Role Overview : Experienced Technical Project Manager to lead the end-to-end delivery of complex AI/ML programs. The role combines strong program governance with technical fluency across the AI/ML lifecycle, driving alignment from strategy through production adoption and value realization. Key Responsibilities • Lead end-to-end delivery of multiple, complex AI/ML programs. • Drive alignment across Business, Data, Data Science, Technology, and leadership teams. • Define program roadmap, governance, success metrics, and delivery strategy. • Translate strategic priorities into executable AI initiatives. • Proactively manage cross-project dependencies, risks, and escalations. • Drive production implementation, adoption, and value realization. • Provide leadership visibility through structured reporting and governance forums. • Establish delivery standards and mentor junior program managers. Required Skills & Qualifications • 5–7 years of experience delivering technical/AI/ML programs. • Strong understanding of the AI/ML lifecycle, data platforms, and responsible AI practices. • Proven ability to manage senior stakeholders and cross-functional teams. • PMP / Agile certification preferred; proficiency with tools such as Jira, MS Project, or Azure DevOps. • Excellent communication, leadership, and problem-solving skills. Requirements: • 5–7 years of experience delivering technical/AI/ML programs. • Strong understanding of the AI/ML lifecycle, data platforms, and responsible AI practices. • Proven ability to manage senior stakeholders and cross-functional teams. • PMP / Agile certification preferred; proficiency with tools such as Jira, MS Project, or Azure DevOps. • Excellent communication, leadership, and problem-solving skills. Responsibilities: Lead end-to-end delivery of multiple, complex AI/ML programs. • Drive alignment across Business, Data, Data Science, Technology, and leadership teams. • Define program roadmap, governance, success metrics, and delivery strategy. • Translate strategic priorities into executable AI initiatives. • Proactively manage cross-project dependencies, risks, and escalations. • Drive production implementation, adoption, and value realization. • Provide leadership visibility through structured reporting and governance forums. • Establish delivery standards and mentor junior program managers.