Global Engineering AI Solutions Manager

Global Engineering Ai Solutions Manager

As a Global Engineering AI Solutions Manager, the role will lead the design, implementation, and support of AI-driven solutions within the Oracle SCM ecosystem to automate processes, improve operational efficiency, and enable data-driven decision-making across the product lifecycle. The position focuses on leveraging agentic AI systems that integrate large language models (LLMs), enterprise data, APIs, and orchestration frameworks to deliver secure, scalable, and context-aware solutions.

The role will ensure alignment between AI capabilities and Product Lifecycle Management (PLM) processes, including product data governance, engineering change management, cross-functional collaboration, and supply chain integration. Experience building AI agents, particularly with exposure to Oracle Product Development Cloud, is considered an added advantage.

Responsibilities:

• Lead the design, configuration, and deployment of AI-driven agents that can reason, plan, and execute multi-step tasks to support product lifecycle and supply chain processes.
• Develop and manage LLM-based prompt orchestration and agent workflows to enhance automation, decision support, and knowledge access across PLM operations.
• Oversee the implementation and continuous improvement of Oracle Cloud solutions, leveraging AI-driven automation to streamline product development, engineering change, and product data management processes.
• Ensure seamless integration of AI capabilities with Oracle SCM, PLM modules, and third-party enterprise applications to enable end-to-end digital product lifecycle connectivity.
• Configure and optimize AI agent behaviors using Oracle-native tools, workflows, and APIs, ensuring alignment with enterprise PLM standards and governance.
• Translate complex business and product lifecycle requirements into scalable, AI-enabled solutions that improve operational efficiency and product data visibility.
• Monitor, optimize, and troubleshoot AI agent performance, ensuring reliability, accuracy, and continuous improvement of AI-enabled processes.
• Establish and enforce data governance, security, and compliance frameworks for AI implementations across global PLM systems.
• Collaborate closely with engineering, product development, supply chain, IT, and business stakeholders to drive adoption of AI-enabled PLM capabilities.
• Provide technical documentation, knowledge transfer, and operational support to ensure sustainable deployment and adoption of AI-driven solutions.
• Implement Retrieval-Augmented Generation (RAG) frameworks leveraging structured and unstructured enterprise data to enable intelligent search, insights, and decision support within PLM and Oracle SCM environments.

Requirements:

• Bachelor's degree in information technology, Process Management, or a related field, or equivalent experience
• 15+ years of experience working with Oracle Fusion and enterprise systems, including hands-on exposure to integrations and customizations using REST APIs and related integration frameworks.
• Exposure to Oracle AI Agent Studio or similar enterprise AI platforms for designing and managing AI-enabled workflows.
• Ability to conceptualize and guide the development of AI agent frameworks such as supervisor, sequential, and workflow-based agents to support enterprise automation.
• Strong understanding of enterprise Generative AI technologies and Large Language Models (LLMs) and their application within business and product lifecycle management processes.
• Experience applying prompt engineering techniques for structured enterprise use cases, including grounding AI responses with enterprise data, and implementing Retrieval-Augmented Generation (RAG) frameworks.
• Practical understanding of LLM limitations, including hallucination risks, with the ability to establish mitigation strategies and validation controls.
• Solid knowledge of enterprise AI security, governance, and compliance standards to ensure responsible and controlled AI adoption.
• Experience defining role-based access controls, approval workflows, and human-in-the-loop governance models for AI-enabled processes.
• Familiarity with data privacy regulations, access management,…