Manager, Software Engineering – Enterprise AI

Job description

**Manager, Software Engineering – Enterprise AI** **About T-Mobile** T-Mobile US, Inc. (NASDAQ: TMUS), headquartered in Bellevue, Washington, is America’s supercharged Un-carrier, connecting millions through its strong nationwide network and flagship brands, T-Mobile and Metro by T-Mobile. Customers benefit from an unmatched combination of value, quality, and exceptional service experience. **TMUS Global Solutions** TMUS Global Solutions is a world-class technology powerhouse accelerating the company’s global digital transformation. With a culture built on growth, inclusivity, and global collaboration, the teams here drive innovation at scale, powered by bold thinking. **About the Role** This role leads and manages the AI engineering team that serves as the build arm of T-Mobile's Forward Deployed Engineer (FDE) organization — responsible for designing, building, deploying, and scaling advanced AI systems, autonomous agents, and intelligent automation across the enterprise. The Manager oversees a multi-level engineering team of AI Engineers, Senior Engineers, and Principal Engineers, driving execution of the AI engineering roadmap while cultivating a high-performing, innovative engineering culture. Partnering closely with US-based FDEs, Product Management, Architecture, and business stakeholders, this individual translates AI strategy into delivered capabilities — agentic AI workflows, multi-agent orchestration, RAG pipelines, and enterprise platform integrations — while matching engineering capacity to the highest-ROI opportunities across lines of business. The Manager owns delivery across the full AI lifecycle from prototyping through production and continuous optimization, establishing the engineering standards, governance, and operational practices that keep T-Mobile's AI capabilities best-in-class. This role is accountable for headcount planning, talent development, performance management, vendor coordination, and cross-functional collaboration. 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! **What You’ll Do** *Team Leadership & Talent Development* - Lead, mentor, and grow a multi-level team of AI Engineers, Senior Engineers, and Principal Engineers. - Drive performance management, goal setting, coaching, and career development. - Build an engineering culture focused on accountability, quality, collaboration, and innovation. - Own headcount planning, hiring, onboarding, and skill development aligned to the AI roadmap. ***Delivery Ownership*** - Own end-to-end delivery of enterprise AI initiatives — agentic AI systems, multi-agent orchestration, RAG pipelines, and LLM-based solutions — managing roadmaps, sprint planning, risk mitigation, and cross-team dependencies. - Partner with US-based FDEs to match engineering capacity to prioritized, ROI-driven demand across lines of business. - Establish and enforce engineering standards, governance frameworks, and reusable design patterns across the team. - Drive release planning, sprint governance, and deployment quality across environments. ***Operations & Continuous Improvement*** - Own the production support model for deployed AI solutions, including incident management, performance, cost, and output-quality monitoring. - Drive improvements in development practices — team structure, process, tooling, security, and compliance — to enhance efficiency. ***Stakeholder Engagement*** - Partner with Product Management, Architecture, Data Science, and business stakeholders to define priorities and align team output with enterprise AI strategy and ROI targets. - Coordinate offshore scrum teams and vendor/contractor relationships, ensuring consistent quality and velocity across onshore and offshore resources. - Provide executive-level updates on delivery progress, platform health, and value realization. **What You’ll Bring** - Bachelor's degree plus 5 years of related experience; or advanced degree with 3 years; or equivalent combination of education and experience — including experience leading software or AI engineering teams. - Technical understanding of LLM architectures, agentic AI, multi-agent orchestration, RAG pipelines, prompt engineering, fine-tuning, and applied GenAI — sufficient to guide architectural decisions, evaluate trade-offs, and conduct meaningful design reviews. - Experience in Agile/Scrum delivery management — sprint planning, backlog prioritization, capacity planning, velocity tracking — across distributed onshore/offshore teams. - Understanding of enterprise platform ecosystems and how AI solutions integrate via connectors (e.g., MCP), API gateways, and secure integration patterns in regulated environments. - Excellent communication and influencing skills to partner with senior leadership, product, architecture, data science, and business stakeholders. - Experience defining team roadmaps, setting OKRs/KPIs tied to business outcomes (ROI, adoption, productivity), and managing headcount and budgets. - Proven ability to lead global teams and manage cross-functional stakeholders. **Must Have Skills** - 5+ years of software or AI engineering experience, including 2+ years in a people management or engineering leadership role. - Working technical depth in LLM-based systems — agentic workflows, multi-agent orchestration, and RAG. - Experience managing Agile delivery across distributed onshore/offshore teams. - Experience partnering with product, architecture, and business stakeholders to align delivery with ROI targets. **Nice-to-Have** - Experience leading AI platform build-out or multi-phase transformation initiatives. - Familiarity with connector/tool-use patterns (e.g., MCP) and API gateway integration. - Experience with DevOps/CI-CD practices for AI/ML deployments. - Relevant AI/ML, cloud, or program management certifications. - Experience in telecom or large, co