Global Product Owner - Generative AI - Unstructured Data

Embark on a journey where your unique contributions are celebrated, and your professional growth is embraced. At ADCB, we nurture a diverse, inclusive community where every voice is valued. About the business area GBS is a group of highly skilled and talented professionals who form an essential part of ADCB's continued journey of success. With a proud history of commitment, innovation and delivery, GBS constantly strives for excellence whilst ensuring the highest standards of quality and risk awareness. Each and every member of the GBS family plays an integral role in driving ADCB's strategy, growth and digital evolution by working closely with our valued business partners to achieve exceptional customer experience through our outstanding service and support. We are actively seeking an ambitious professional to join our Group Business Service team at ADCB to work alongside passionate colleagues who share your ambition to redefine excellence in UAE banking. In this role, your key responsibilities include: Define and drive the product roadmap for Generative Artificial Intelligence capabilities focused on unstructured data, aligned to the Bank’s artificial intelligence and data strategies, in order to prioritise delivery that meets enterprise needs and aligns with agreed technology direction. Own and maintain ADCB’s approved house view on Generative AI knowledge systems to ensure consistent and controlled adoption of approaches including Retrieval Augmented Generation (RAG), GraphRAG, metadata and chunking strategies, access control, privacy requirements and source attribution. Lead cross functional delivery squads in partnership with AI engineering peers and relevant stakeholders to deliver secure, compliant and scalable capabilities, ensuring product requirements are translated into clear outcomes and delivery is progressed through defined governance and approvals. Establish and apply evaluation frameworks for safety, reliability and performance of Generative AI knowledge systems, including RAG and agent-based implementations, in order to ensure solutions are fit for purpose and aligned with Bank standards. Execute pre-implementation testing in collaboration with specialist evaluation, risk, compliance, legal and information security stakeholders to validate expected behaviours, limitations and control requirements. Ensure runtime guardrails are defined and implemented to manage risk exposures relating to confidentiality, data leakage, prompt injection, hallucination and inappropriate outputs. Integrate observability tools and dashboards to monitor quality, usage, performance trends, risk indicators and adherence to approved standards, enabling structured reporting and timely intervention Own and manage multi squad product backlogs to ensure prioritisation is aligned to business value, delivery capacity and agreed sequencing across dependent teams. Translate the product roadmap into a structured portfolio of deliverables with clear outcomes, milestones and acceptance expectations in order to enable consistent execution across squads. Facilitate agile product ceremonies across squads and ensure consistent governance of prioritisation, refinement and delivery commitments. Resolve cross platform and cross team dependencies by coordinating with relevant owners and partners to remove delivery blockers and manage tradeoffs. Drive delivery progress, quality outcomes and value realisation through transparent reporting on scope, risks, decisions and delivery health, ensuring delivery aligns with approved standards and enterprise constraints. Act as the primary interface between AI engineering teams and senior business stakeholders to ensure shared understanding of priorities, decisions and delivery outcomes. Translate Generative AI capabilities into clear business narratives and outcome statements, ensuring stakeholders understand what is being delivered, the intended use cases and the required operating guardrails. Structure and communicate product value, delivery progress, risks and dependencies to enable informed decision making and prioritisation within agreed governance forums. Present product vision, roadmap progress and impact updates to senior management in a concise and evidence-based manner, ensuring alignment with Bank objectives and timely escalation of issues requiring leadership input, approvals or risk decisions. Evaluate emerging trends in Generative AI and unstructured data approaches, including advances in Large Language Models (LLM), Retrieval patterns, Reinforcement Learning from Human Feedback (RLHF) and Agentic Systems, in order to identify opportunities that are relevant and viable within the Bank context. Support the adoption of approved tools and platforms such as Azure OpenAI, LangChain and vector database capabilities in line with Bank standards and architectural direction.Promote controlled experimentation and learning through defined proof of value initiatives, ensuring outcomes, constrai

Define and drive the product roadmap for Generative Artificial Intelligence capabilities focused on unstructured data, aligned to the Bank’s artificial intelligence and data strategies, in order to prioritise delivery that meets enterprise needs and aligns with agreed technology direction. Own and maintain ADCB’s approved house view on Generative AI knowledge systems to ensure consistent and controlled adoption of approaches including Retrieval Augmented Generation (RAG), GraphRAG, metadata and chunking strategies, access control, privacy requirements and source attribution. Lead cross functional delivery squads in partnership with AI engineering peers and relevant stakeholders to deliver secure, compliant and scalable capabilities, ensuring product requirements are translated into clear outcomes and delivery is progressed through defined governance and approvals. Establish and apply evaluation frameworks for safety, reliability and performance of Generative AI knowledge systems, including RAG and agent-based implementations, in order to ensure solutions are fit for purpose and aligned with Bank standards. Execute pre-implementation testing in collaboration with specialist evaluation, risk, compliance, legal and information security stakeholders to validate expected behaviours, limitations and control requirements. Ensure runtime guardrails are defined and implemented to manage risk exposures relating to confidentiality, data leakage, prompt injection, hallucination and inappropriate outputs. Integrate observability tools and dashboards to monitor quality, usage, performance trends, risk indicators and adherence to approved standards, enabling structured reporting and timely intervention. Own and manage multi squad product backlogs to ensure prioritisation is aligned to business value, delivery capacity and agreed sequencing across dependent teams. Translate the product roadmap into a structured portfolio of deliverables with clear outcomes, milestones and acceptance expectations in order to enable consistent execution across squads. Facilitate agile product ceremonies across squads and ensure consistent governance of prioritisation, refinement and delivery commitments. Resolve cross platform and cross team dependencies by coordinating with relevant owners and partners to remove delivery blockers and manage tradeoffs. Drive delivery progress, quality outcomes and value realisation through transparent reporting on scope, risks, decisions and delivery health, ensuring delivery aligns with approved standards and enterprise constraints. Act as the primary interface between AI engineering teams and senior business stakeholders to ensure shared understanding of priorities, decisions and delivery outcomes. Translate Generative AI capabilities into clear business narratives and outcome statements, ensuring stakeholders understand what is being delivered, the intended use cases and the required operating guardrails. Structure and communicate product value, delivery progress, risks and dependencies to enable informed decision making and prioritisation within agreed governance forums. Present product vision, roadmap progress and impact updates to senior management in a concise and evidence-based manner, ensuring alignment with Bank objectives and timely escalation of issues requiring leadership input, approvals or risk decisions. Evaluate emerging trends in Generative AI and unstructured data approaches, including advances in Large Language Models (LLM), Retrieval patterns, Reinforcement Learning from Human Feedback (RLHF) and Agentic Systems, in order to identify opportunities that are relevant and viable within the Bank context. Support the adoption of approved tools and platforms such as Azure OpenAI, LangChain and vector database capabilities in line with Bank standards and architectural direction. Promote controlled experimentation and learning through defined proof of value initiatives, ensuring outcomes, constraints