Overview
Leads the strategic vision, backlog prioritization, and execution of next-generation, AI-enabled digital solutions for the institution’s financial management landscape. Drives the digital transformation of financial governance, fiduciary controls, audit readiness, and financial reporting.
Key Responsibilities
- Define and execute an end-to-end product strategy embedding AI, ML, and IPA into operational financial workflows.
- Align product roadmaps with institutional financial policies, business strategies, and emerging technology trends.
- Evaluate emerging AI technologies, Generative AI models, and LLM orchestration tools.
- Maintain, refine, and prioritize the product backlog for AI-driven financial tools.
- Translate complex financial operations and machine learning workflows into actionable user stories.
- Oversee the end-to-end model delivery lifecycle (MLOps/LLMOps).
- Ensure AI models and automated workflows adhere to institutional risk management, data privacy, cyber security, and audit standards.
- Support development of Responsible AI frameworks.
- Partner with internal and external auditors.
- Support modernization of end-to-end financial management systems.
- Design AI-driven anomaly detection engines.
- Leverage NLP and RAG to automate extraction and validation of unstructured financial data.
- Collaborate with data engineering and enterprise architecture teams.
- Ensure high standards of data governance, lineage, cleanliness, and data readiness.
- Serve as the primary liaison connecting Financial Management Specialists, Accountants, Auditors, Treasury Officers, and Information Technology delivery teams.
- Drive change management strategies to promote organizational adoption of AI tools.
Required Experience
- Minimum of 8 years of relevant experience with a Master’s Degree in Computer Science, Data Science, Artificial Intelligence, Information Systems, Finance, or a related field; OR a minimum of 10 years of progressive experience in AI product management, financial technology, or digital transformation with a Bachelor’s Degree.
- Demonstrated track record as a Product Owner or Product Manager successfully shipping data-intensive or AI/ML-driven enterprise applications.
- Hands-on experience with the machine learning lifecycle, model deployment pipelines, data drift monitoring, and evaluation metrics for deterministic vs. probabilistic systems.
- Proficiency in cloud data architectures (Azure, AWS, or GCP), SQL, data warehousing, API integrations, and modern data platforms (e.g., Databricks, Snowflake).
- Demonstrated familiarity with enterprise financial systems (e.g., SAP, Oracle Financials) and core accounting concepts, internal controls, and auditing frameworks.
- Experience building and deploying Large Language Model (LLM) agents or advanced copilot tools within regulated financial environments (plus point).
- Hands-on programming or prototyping experience (e.g., Python, R, SQL) for rapid data exploration and feasibility analysis (plus point).
- Deep knowledge of international accounting standards (IFRS/IPSAS), public sector financial management, or World Bank Group operational financial policies (plus point).
Qualifications
- Master’s Degree in Computer Science, Data Science, Artificial Intelligence, Information Systems, Finance, or a related field; OR a Bachelor’s Degree.
- Active certification in Agile methodologies (e.g., Certified SAFe Product Owner/Product Manager, Certified Scrum Product Owner) preferred.
