Senior Manager - Investment, PLM & Document Intelligence Platforms

Requirements

• Bachelor's or master's degree in Technology, Engineering, Data/AI, Finance, or a related field. «TO CONFIRM» Masdar's preferred certifications.
• Preferred Experience:
• 14-18+ years in enterprise systems and product/platform ownership (elevated from the source roles to reflect the combined senior mandate).
• Proven end-to-end deployment of PLM and project-based ERP systems (e.g., IFS Cloud / IFS Project Lifecycle, SAP S/4HANA Projects, Oracle Projects / Primavera) across Design → Build → Integration → Go-Live → Optimization.
• Job-Specific Skills:
• 6+ years in the control-based document ecosystem (enterprise SharePoint, Microsoft Syntex) or Equivalent and 5+ years delivering enterprise document-transformation programs.
• Hands-on experience building AI-driven document workflows and agent-based orchestration (Azure OpenAI / Copilot / multi-agent frameworks), with the identity, guardrail, and audit rigor expected of financial-grade AI platforms.
• Investment lifecycle and M&A processes; capital project development and construction lifecycle; financial planning and portfolio reporting.
• Role is to be based in Abu Dhabi, UAE.
• As part of the application process, we will collect, store and process personal information about you.
• Masdar will use your personal information in accordance with our Candidate Privacy Notice , which provides details on the purposes for which your data is processed.

Additional Information

To own the end-to-end digital thread from deal origination to asset performance, together with the document-intelligence layer that turns Masdar's contracts, engineering records, and due-diligence files into structured, decision-ready data - enabling "Documents → Data → Insight → Financial Decision." Also serves as the product owner and execution lead for Masdar's investment lifecycle and product lifecycle management platforms, spanning deal origination through asset performance. Key Accountabilities : Own the end-to-end platform portfolio across investment planning, engineering design, permitting, tendering, project execution, asset and pipeline management. Own enterprise document and contract-lifecycle platforms (Legal / CLM, engineering document control, M&A and due-diligence documentation). Define and maintain a single product roadmap aligned to business priorities, treating the investment lifecycle and its supporting documents as one digital thread. Ensure compliance, traceability, and governance across the transactional platforms and the document estate. Deploy AI-driven document workflows: ingestion of structured and unstructured data, extraction of key financial and legal fields, normalization, classification, summarization, and reasoning. Enable Human-in-the-Loop approvals and agent-to-agent orchestration across enterprise systems. Partner with Domain Architecture, Infrastructure, and Security to ensure agent identity and guardrails as workflows scale - consistent with governed AI-platform practice at Goldman Sachs and JPMorgan Chase Deliver platforms providing portfolio visibility, capital allocation insight, and scenario modeling for investments. Enable M&A due-diligence workflows, capital planning and approvals, project / construction tracking, and asset / portfolio performance. Partner closely with Finance, Investment, and M&A teams to connect document evidence to capital decisions. Integrate across ERP core (SAP / Oracle), procurement, asset management, document management, and EPC / O&M source systems. Build the enterprise-wide knowledge layer for a unified, origination-to-operations view. Lead Agile delivery through system integrators and SaaS vendors with structured release cycles and continuous improvement. Deliver operational and portfolio reporting via SaaS-native tooling and Power BI; partner with the AI Products & Analytics Platforms team for advanced insight. Manage system integrators, SaaS/ERP vendors (e.g., IFS, SAP, Oracle), Microsoft ecosystem partners, and AI vendors. Enforce SLAs, KPIs, and business outcomes; apply FinOps-style cost discipline on platform and AI spend.

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