Job Summary

Lead the end-to-end delivery of AI, Machine Learning, and Generative AI initiatives, ensuring successful execution against business and strategic objectives.

Skills and Competencies

- 5-10 years of experience leading the delivery of AI, Machine Learning, or Generative AI initiatives within complex enterprise environments

- Strong expertise in Agile delivery methodologies, including Scrum and Kanban, with the ability to coach teams and drive continuous improvement

- Proven experience managing product backlogs, prioritizing workstreams, and aligning scope, timelines, and quality objectives across multiple teams

- Excellent stakeholder management and communication skills, with the ability to influence decisions, manage risks, and provide clear delivery updates to senior leaders

- Robust understanding of project governance, delivery reporting, and Agile tools such as Jira and Confluence

- Preferred: Familiarity with data science workflows, AWS, enterprise-scale AI deployments, and cross-functional, global team collaboration

- Knowledge of financial analysis and broader finance concepts is advantageous

Education

- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline. Business-related degrees will also be considered when supported by relevant technical experience

- Professional certifications such as PMP, AWS Certified Cloud Practitioner, Scrum Master, SAFe, or equivalent Agile and delivery certifications are preferred

Responsibilities

- Lead the end-to-end delivery of AI, Machine Learning,



and Generative AI initiatives, ensuring successful execution against business and strategic objectives

- Develop and manage delivery plans, coordinate cross-functional dependencies, and drive the timely release of high-quality product increments

- Partner with product, engineering, analytics, and data science teams to prioritize roadmaps, support quarterly planning, and align execution with business goals

- Champion Agile delivery practices by facilitating Sprint ceremonies, retrospectives, planning sessions, and continuous improvement initiatives

- Build strong relationships with stakeholders across business and technology functions, providing visibility into progress, risks, dependencies, and outcomes

- Support product lifecycle activities, including pilot programs, product launches, user feedback collection, and adoption initiatives

- Proactively identify delivery risks, implement mitigation strategies, and drive quality standards throughout the development lifecycle

- Collaborate with Data Science, MLOps, Engineering, and Product teams to enhance delivery processes, accelerate time-to-market, and ensure scalable AI solutions and contribute to the evolution of AI-enabled products by translating business needs into actionable delivery plans and measurable outcomes

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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