Job Description & How to Apply Below
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.
About 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.
TMUS India Private Limited operates as TMUS Global Solutions.
About the Role:
This role leads one or more software engineering teams responsible for building and operating a highly reliable, scalable Customer Data Platform (CDP) that powers analytics, AI/ML, and customer-facing experiences. The Software Engineering Manager is accountable for delivery quality, system reliability, and engineering excellence, while embedding AI/ML-driven capabilities and AI-assisted engineering practices into daily work. The role balances people leadership, technical depth, and execution rigor to ensure the platform meets enterprise standards for performance, data integrity, security, and compliance.
Success is measured by predictable delivery, platform stability, customer data trust, and adoption of AI-enabled solutions. The work directly impacts how the organization understands, serves, and personalizes experiences for millions of customers.
What You’ll Do:
Engineering Leadership & Delivery Excellence:
Lead, mentor, and grow high-performing software and data engineers responsible for the Customer Data Platform
Establish clear expectations for engineering quality, reliability, testing, and operational readiness
Own delivery outcomes including scope, timelines, risk management, and execution predictability
Drive adoption of AI-assisted development tools to improve code quality, velocity, and consistency
Platform & Architecture Ownership:
Oversee the design and evolution of scalable CDP architectures supporting batch, streaming, and AI-driven workloads
Ensure systems meet enterprise requirements for availability, performance, security, and cost efficiency
Partner with architects and principal engineers to guide technical direction and modernization efforts
AI/ML & Intelligent Data Capabilities:
Lead teams building AI-enabled data capabilities, including:
LLM-powered services, prompt engineering, and agentic workflows
Retrieval-Augmented Generation (RAG) using Vector Databases
ML lifecycle management using MLflow and MLOps best practices
Ensure responsible AI practices including testing, validation, monitoring, and data auditing
Drive practical adoption of Azure OpenAI, Lang Chain / Lang Graph, and modern AI frameworks within the CDP
Data Quality, Identity & Customer Resolution:
Ensure high-quality customer data through robust entity resolution and identity graph solutions
Oversee implementation of deterministic, probabilistic, and fuzzy matching techniques at scale
Enforce strong practices for data validation, auditing, lineage, and error handling
Champion platform-level ownership of customer data trust and correctness
Cross-Functional Collaboration & Stakeholder Alignment:
Partner with Product, Analytics, Security, Privacy, and Business teams to translate requirements into reliable platform capabilities
Communicate delivery status, risks, and trade-offs clearly to leadership and stakeholders
Align roadmap priorities with business outcomes and platform health
Operational Excellence & Continuous Improvement:
Promote CI/CD & CDP, automated testing, observability, and on-call readiness
Drive continuous improvement through retrospectives, metrics, and engineering standards
Support additional initiatives as needed to advance platform maturity
What You’ll Bring :
Bachelor’s Degree
7 to 10 years of related work experience OR combination of education and experience deemed equivalent
Must Have
Skills:
7 to 10 years of professional software engineering experience, including building large-scale data or platform systems
3 to 5 years of people…
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