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About the role
Job Summary As the AI Delivery Transformation Lead within the Application Development & Modernization (ADM) Business Unit at Malomatia, you will drive the transformation of delivery by embedding AI into day-to-day project execution. Working in partnership with the Delivery Unit Leads for Application Development, Application Management, and Quality Engineering, you will identify, institutionalize, and scale AI-driven practices that improve delivery quality, optimize costs, and enhance productivity within each Delivery Unit. This role owns the standardization layer for AI adoption across ADM, including tooling decisions, playbooks, enablement programs, and the KPI framework, while adoption and value realization within each Delivery Unit is jointly owned with the respective Delivery Unit Lead. Internal Interface BU Director - ADM Practice Head ADM Delivery Unit Leads (Application Development, Application Management, Quality Engineering) Engineering Teams Project Managers IT / Security External Interfaces Vendors providing Ai subscriptions Drive transformation of delivery across ADM by embedding AI into day-to-day project execution, working in partnership with Delivery Unit Leads (Application Development, Application Management, Quality Engineering) to identify, institutionalize, and scale AI-driven practices that improve delivery quality, optimize costs, and enhance productivity within each Delivery Unit. Owned by this role: Identify and prioritize high-impact AI use cases across the ADM delivery lifecycle (Dev, QA, Support, DevOps), drawing on cross-DU patterns and POC outcomes. Finalize and standardize AI tools and platforms based on POCs and enterprise direction. Develop and execute role-based AI learning paths and enablement programs. Create reusable AI playbooks, templates, and accelerators. Establish the KPI framework and tracking mechanism for AI adoption and value realization across DUs. Joint with Delivery Unit Leads (Application Development, Application Management, Quality Engineering): Drive adoption of AI tools within delivery workflows for each Delivery Unit. Define and institutionalize AI-first delivery patterns and standard practices within each DU. Track progress against KPIs for productivity, cost optimization, and quality improvement at the DU level. Drive measurable value realization and continuous improvement within each DU.
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