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 environments
Develop 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 operations
Integrate AI capabilities with internal APIs, enterprise platforms, and user-facing applications in IT and Networks, working with LLM-based and agentic workflows
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Explore business processes and testing workflows to identify where AI and automation can make a real impact on test coverage, stability, and cycle time.
Develop practical recommendations and roadmaps; learn to define expected value, risks, and success metrics.
Collaborate on proof-of-concept (PoC) projects that showcase the business value of AI-enabled testing, such as predictive test selection, defect risk modeling, and intelligent test data generation.
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