AI Senior Rollout and Support Manager

💼 Role OverviewAs an AI Senior Rollout and Support Manager, you'll lead the design and deployment of end-to-end AI solutions that are robust, scalable, and span data ingestion, model deployment, API orchestration, and business system integration across hybrid cloud and on-premises environments. This role offers an exciting opportunity to grow your expertise in AI platform development while making a meaningful impact on our organization's digital transformation.🎯 What you will do (Key Responsibilities)Lead the planning, testing, and delivery of solutions for the MA Global AI self-service platform, including Agentic AI, AI Workbench and Tooling, Model Management, shared RAG service, MCP, and AI Runtime environmentsDevelop solution blueprints by translating business requirements into technical architecture, gaining hands-on experience in selecting appropriate tools, frameworks, and infrastructure for AI model development and operationsIntegrate AI capabilities with internal APIs, enterprise platforms, and user-facing applications in IT and Networks, working with LLM-based and agentic workflowsCollaborate with security and governance teams to ensure solutions are secure and compliant, embedding PDPA and enterprise policy requirements into your designsPartner with MA AI and data teams to operationalize AI models, learning how to ensure architectural alignment, scalability, and lifecycle supportContribute to proof-of-concepts (PoCs), technical evaluations, and prototyping efforts, gaining valuable experience in emerging AI technologiesStay current with AI technologies and best practices in integration, model lifecycle management, and platform operationsParticipate actively in architecture reviews, technical discussions, and sprint planning with cross-functional teamsDefine and enforce architectural standards, reusable design patterns, open standards, and reference implementations to streamline AI deployment across business unitsExplore emerging AI technologies such as vector databases, context-aware agents, and orchestration protocols (e.g., LangChain, LangGraph, MCP, A2A), and assess their applicability within the enterpriseLead solutioning activities and mentor a small development team consisting of AI engineers and application developers on selected use casesOwn the business knowledge strategy for AI, including documents, data, FAQs, and rules; coordinate with data owners and regions for knowledge onboardingDrive improvements in AI quality through prompt optimization, knowledge management, and feedback loopsSupport the auto-learning framework and guide the organization in adopting the self-service AI Framework and API interface.👤 What We’re Looking For (Qualifications & Skills)Bachelor's degree in computer science, engineering, data, AI/ML, or related field (master's degree preferred).3+ years of experience in solution management, AI/ML platform integration, data pipeline design, or API-driven systems, or equivalent project-based experience.Experience designing and integrating AI workflows, including exposure to data pipelines, model orchestration, and API serving across cloud environments.Understanding of AI/ML systems, cloud-native architectures, and API ecosystems, with willingness to deepen expertise.Hands-on or project experience with cloud-based AI services such as Microsoft Azure ML, AI Foundry, BTP AI Core, or Bedrock, including model deployment and monitoring.Familiarity with open-source and open-standard tooling for AI and agentic frameworks (e.g., n8n, Portkey, or equivalent).Knowledge of API architecture and integration standards, with experience enabling secure and scalable interfaces between AI models and enterprise systems.Ability to evaluate and learn new AI technologies, frameworks, and vendor solutions for enterprise environments.Strong collaboration and communication skills to work effectively across data, API, ML, and AI platform teams, translating between business and technical stakeholders.Solid project management competencies and organizational skills.Good technical and presentation skills, with the ability to explain complex concepts clearly to diverse audiences.Proactive mindset and eagerness to learn emerging technologies and industry trends.Foundational knowledge of business processes and data-driven use cases, with genuine interest in AI and data technologies.