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ecosystem. The Manager over sees a multi – level engineering team comprising AI Engineers, Senior Engineers, and Principal Engineers, driving execution of the AI engineering roadmap while cultivating a high – performing, innovative engineering culture. This individual partners with Product Management, Architecture, Data Science, and business stakeholders to translate AI strategy into delivered capabilities — including agentic AI workflows, multi – agent orchestration systems, RAG pipelines, and enterprise platform integrations . The Manager owns team delivery across the full AI lifecycle from experimentation and prototyping through production deployment and continuous optimization, establishing engineering standards, governance frameworks, and operational exce llence practices. This role is accountable for headcount planning, talent development, performance management, vendor coordination, and team collaboration to ensure T – Mobile’s AI engineering capabilities remain best – in – class.</p><p>We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact!</p><p><strong>What You’ll Do:</strong></p><ul><li>Drive improvements in development practices, including team structure, processes, tooling, security, and compliance to enhance efficiency 20 % Own end – to – end delivery of enterprise AI initiatives including agentic AI systems, multi – agent orchestration platforms, RAG pipelines, and LLM – based solutions, managing execution roadmaps, sprint planning, risk mitigation, and cross – team dependencies.</li><li>Partner with Product Management, Architecture, and business stakeholders to define AI engineering priorities, translate complex business requirements into technical initiatives, and ensure alignment between team output and enterprise AI strategy and ROI targets.</li><li>Coordinate and manage offshore scrum teams and vendor/contractor relationships, overseeing distributed delivery models, knowledge transfer, and ensuring consistent engineering quality and velocity across onshore and offshore resources.</li><li>Partner with Product Management, Architecture, and business stakeholders to define AI engineering priorities, translate complex business requirements into technical initiatives, and ensure alignment between team output and enterprise AI strategy and ROI targets.</li></ul><p><strong>What You’ll Bring:</strong></p><ul><li>Bachelor's Degree plus 5 years of related work experience or Advanced degree with 3 years of related experience</li><li>technical understanding of LLM architectures, agentic AI systems, multi – agent orchestration, RAG pipelines, prompt engineering, fine – tuning, and applied GenAI — sufficient to guide architectural decisions, evaluate technical trade – offs, and conduct meaningful design reviews.</li><li>in Agile/Scrum delivery management, including sprint planning, backlog prioritization, capacity planning, velocity tracking, and managing execution across distributed onshore/offshore teams.</li><li>of enterprise platform ecosystems and how AI solutions integrate via MCP connectors, API gateways, and secure integration patterns within regulated environments.</li><li>education, experience, and skills required or preferred to perform the essential functions of the job. 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