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This role leads engineering teams that design, build, and operate enterprise-grade applications and digital products within an Agile, automation-first delivery model. The teams work across the full stack—Java/Spring Boot, Angular/React, Python, APIs, and data-enabled platforms—and increasingly leverage agentic AI workflows (autonomous code generation, AI-assisted testing, intelligent pipeline orchestration) to multiply velocity and reduce manual toil. This is a people-leadership role with an engineering backbone—the Sr Manager sets technical direction, makes architecture trade-off decisions, coaches engineers, and holds the quality bar, but spends the majority of time leading teams rather than writing production code. Success is measured by delivery throughput, team health and retention, engineering cycle time reduction, and the ability to run a lean organization that ships more with less through smart automation. The work directly impacts T-Mobile's product velocity, customer experience, and operational scalability.
Job Responsibility:
Lead and manage cross-functional engineering teams (software engineers, QA, DevOps, data engineers, product managers) to deliver enterprise applications—providing technical direction, architecture guidance, coaching, and performance management
Build and evolve an agentic AI capability within the engineering org—standing up AI-assisted workflows (automated code generation, test creation, Jira-to-MR pipelines) that reduce cycle time and free engineers for high-judgment work
Define and drive continuous improvement and engineering excellence—CI/CD pipeline optimization, automated quality gates, tech debt management, and measurable productivity frameworks (DORA metrics, automation coverage)
Own the technical roadmap in collaboration with architecture, platform engineering, cybersecurity, and design teams—balancing feature delivery, platform modernization, and automation investment
Manage technical vendor relationships and evaluate emerging technology (AI/ML tooling, cloud-native platforms, data infrastructure) to keep the engineering stack current and competitive
Recruit, hire, and develop engineering talent who bring strong full-stack fundamentals, a bias toward automation, and the ability to work effectively alongside AI-augmented toolchains
Requirements:
Bachelor's Degree and 7 years of related work experience or a combination of education and experience deemed equivalent Acceptable areas of study include Computer Science, Engineering, IT or equivalent experience
7-10 years experience of developing large scale business systems applications in an agile product development environment with an engineering background across the modern stack (Java, Python, JavaScript/TypeScript, APIs, databases)
2-4 years People leadership managing cross-functional engineering teams (5+ engineers in direct reporting relationships)—including hiring, performance management, career development, and org design
At least 18 years of age
Legally authorized to work in the United States
Nice to have:
2-4 years applying AI/ML concepts or LLM-based tools in production environments
2+ years driving delivery excellence through process improvement, automation, and measurable gains in velocity
2+ years working with big data platforms (e.g., Snowflake, Databricks, Spark, Kafka) and data pipeline operations
1+ year operating in cloud-native/Kubernetes environments with CI/CD and infrastructure-as-code
1+ year experience with API platforms, gateways, or developer ecosystems