Experience

Driving digital transformation initiatives focused on Engineering Digital Twin enablement and Autonomous Operations strategy for ADNOC assets. Responsible for AI/vendor evaluation, digital architecture definition, autonomous operations use-case discovery, roadmap development, and data strategy to enable AI-driven decision-making capability.

• AI & Vendor Technical Leadership — Leading technical discussions with Digital Twin, AI, analytics, and robotics vendors; evaluating solution fit, scalability, cybersecurity compliance, integration feasibility, and measurable operational value.
• Digital Architecture Definition — Designing high-level and logical digital architectures; defining integration frameworks between engineering systems, historian platforms, enterprise systems, and AI layers; reviewing and optimizing vendor-proposed architectures for long-term operational sustainability.
• AI Use-Case & Prototype Framing — Defining L4/L5 autonomous operations use cases, identifying workflows suitable for AI-driven decision-making, and shaping concepts into practical scenarios that vendors and engineering teams can validate.
• Data Strategy & Flow Design — Designing structured data flows (real-time and batch); defining contextualization models and asset hierarchy alignment; ensuring engineering data readiness for AI-driven applications and Digital Twin environments.
• Digital Governance & Standard Alignment — Ensuring compliance with ADNOC digital frameworks and engineering standards; supporting lifecycle data integrity and structured digital handover philosophy.
• Positioned ADNOC assets for advanced autonomous operations through strategic vendor evaluation and architectural alignment with enterprise AI/ML capabilities.
• Established data flow architectures and governance frameworks enabling structured Digital Twin enablement across multiple operational domains.

Agile Product Owner for a globally deployed enterprise engineering software platform used by Oil & Gas operators, EPCs, and industrial enterprises across 50+ countries — owning product outcomes, backlog strategy, sprint delivery, and AI-enabled document intelligence, data automation, and engineering data management features.

• Owned the product backlog end-to-end — writing and refining user stories and epics, prioritising features against business value and client requirements, and managing sprint delivery with cross-functional engineering teams using JIRA and Azure DevOps.
• Used functional prototypes and workflow demos to clarify ambiguous product concepts with engineering teams and enterprise stakeholders before full implementation.
• Led sprint planning, backlog grooming, sprint reviews, and retrospectives across multiple Agile release cycles — maintaining velocity, managing dependencies, and ensuring features met acceptance criteria before release.
• Worked directly with enterprise clients and stakeholders to gather requirements, validate feature delivery, and translate complex technical constraints into clear, actionable user stories.
• Designed and specified AI-enhanced document intelligence workflows — LLM-assisted extraction concepts, hybrid validation pipelines, and structured data management for demanding industrial environments.
• Managed product quality end-to-end: defined test scope, coordinated QA cycles, and owned patch and hotfix release cadence for enterprise clients with zero-tolerance for data errors.
• Document automation features reduced manual review effort by 80% — validated with enterprise Oil & Gas clients.
• Automated validation pipelines improved data quality metrics by 85% in controlled client environments.
• Recognised with 3× Performance Excellence Awards and 2× Project Excellence Awards for delivery on critical product milestones.
• Features shipped to global enterprise clients across Oil & Gas, Power, Chemicals, and Industrial sectors — including UAE and Middle East operations.

Built hands-on domain expertise across P&ID development, SmartPlant Instrumentation (SPI), instrument data sheets, engineering document control, and EPC project data workflows — the technical foundation that informs how I evaluate, scope, and govern digital delivery in industrial environments.

• Delivered instrument data sheets, equipment lists, and technical documentation for Oil & Gas EPC projects — developing deep fluency in how industrial data is structured, reviewed, approved, and handed over across project lifecycles.
• Developed expertise in SmartPlant Instrumentation (SPI) and engineering data management systems — grounding that directly informs how I evaluate and govern digital programme delivery in industrial environments.