Avnet · Kowloon Bay, Hong KongPrepare for this interview
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Job Summary: This role will lead and scale AI and intelligent automation capabilities across APAC, and will be responsible for translating global AI strategies into regional execution, enabling business units to adopt AI safely and effectively, and delivering tangible business value through AI‑powered solutions. This position will report to the Head of IT in APAC. The role will work closely with Global IT AI teams, regional IT functions, and business stakeholders to adopt and extend enterprise AI capabilities such as knowledge search agents, intelligent workflow automation, and AI‑assisted customer interactions. A strong emphasis is placed on governance, standardization, secure deployment, and user enablement, within a Microsoft‑centric technology landscape. This role also plays a key part in uplifting AI literacy across the region and supporting responsible, ethical, and compliant use of AI technologies. Principal Responsibilities: Strategic Leadership & Delivery Define and execute the APAC AI and intelligent automation roadmap aligned with global IT strategy and business priorities. Partner with global AI teams to adopt, localize, and scale enterprise AI solutions for APAC. Identify, prioritize, and deliver high‑impact AI and automation use cases across business functions, including knowledge management, customer operations, and process automation. Research and trial new technologies and assess suitability for business applications. Measure and communicate business value, adoption, and risk posture of AI initiatives. AI Enablement & Adoption Drive safe, secure, and compliant adoption of approved AI platforms and tools, including Microsoft 365 Copilot, Copilot Studio agents, and enterprise AI services. Lead AI enablement initiatives such as training programs, workshops, and agent‑builder communities to improve AI fluency across IT and business teams. Act as a regional advocate and advisor for AI best practices and emerging capabilities. Technical & Platform Leadership Oversee the design and implementation of AI solutions built on Microsoft Azure, ensuring scalability, security, and enterprise integration. Collaborate with data, infrastructure, and application teams to ensure AI solutions are aligned with enterprise architecture standards. Guide the adoption of modern AI engineering practices, including DevSecOps, MLOps, and responsible AI patterns. Governance & Risk Management Represent APAC IT in the Global AI Governance Council, contributing to policies on ethical AI, data privacy, and tool approval. Ensure AI solutions comply with enterprise security, legal, and regulatory requirements. Establish regional AI standards, reference architectures, and reusable patterns in alignment with global guidance. Job Level Specifications: Manages experienced, professional employees and/or supervisors; and/or manages large, complex technical and/or business support teams. Accountable for the performance and results of a team and/or department. Interprets and administers policies, processes and procedures that affect direct reports and the workflow of the team/department. Adapts departmental plans and priorities to address resource and operational challenges. Contributes to budget development and performance standards of department and direct reports. Assignments are defined in the form of objectives. Decisions are guided by policies, procedures, business plans and independent judgment. Collaborates with team(s), customers/ clients, functional peer group managers and occasionally senior management. Participates and presents at meetings with internal and external representatives. Decisions may have impact on work processes and outcomes. Erroneous decisions or recommendations may result in serious delays and considerable expenditures of additional time, people and/or financial resources. Required Skills: Proven experience leading AI, automation, or advanced analytics initiatives in enterprise environments. Strong hands‑on and architectural experience with Microsoft Azure, including: Azure OpenAI Service Azure AI Search Azure Machine Learning Azure Data Lake / Synapse Analytics Databricks Azure DevOps / GitHub Enterprise Power Platform (AI Builder, Power Automate, Copilot Studio) Solid understanding of: Generative AI and large language models (prompting, embeddings, RAG patterns) Machine learning lifecycle and MLOps Data engineering and feature pipelines API‑based system integration Vector databases and semantic search Experience delivering AI use cases that generate measurable business outcomes. Familiarity with AI governance, ethical AI principles, and data privacy frameworks.
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