Principal Engineer, Software - AI Platforms & Network Data

Principal Engineer At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That's how we're UNSTOPPABLE for our employees! Job Overview The Network Data & AI team builds the data platforms, data products, and AI-powered solutions that empower data-driven decisions and transform network operations, customer experience, and engineering productivity across T-Mobile. Our team develops enterprise-scale capabilities that collect, process, analyze, and operationalize network and device data to deliver trusted analytics, intelligent automation, and AI-powered insights. These capabilities enable engineering and business organizations to make faster, better-informed decisions supporting network planning, customer experience, device intelligence, geospatial intelligence, and AI-driven innovation. Our mission is to solve complex engineering challenges by building scalable AI, software, and data solutions that create measurable business value while advancing intelligent automation and engineering excellence. About the Role The Principal Engineer serves as a senior technical leader responsible for designing, building, and evolving enterprise-scale AI, software, and data platforms that power T-Mobile's Network Data & AI initiatives. This role architects intelligent systems that transform network, device, and customer data into trusted data products, AI-powered solutions, and automated workflows supporting engineering, business operations, and executive decision-making. Working at the intersection of artificial intelligence, software engineering, cloud computing, and distributed systems, the Principal Engineer develops reusable AI services and platform capabilities—including Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and enterprise knowledge systems—that accelerate intelligent automation, engineering productivity, and AI adoption across the Network Data & AI organization. This role requires a highly collaborative technical leader who combines hands-on software engineering with strategic architectural thinking to solve complex technical challenges, evaluate emerging technologies, and influence technical direction across multiple engineering teams. Success is measured by delivering scalable, secure, and highly available AI platforms, software solutions, and data products that improve operational efficiency, enable intelligent automation, support strategic business initiatives, and deliver measurable business value. What You'll Do As a Principal Engineer, you will: Lead the architecture, design, and implementation of enterprise-scale AI, software, and data platforms supporting Network Data & AI initiatives. Design and develop cloud-native, distributed systems that transform large-scale network and enterprise data into trusted data products and AI-powered solutions. Build reusable AI services utilizing Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, enterprise knowledge systems, and related technologies. Develop scalable software solutions using modern programming languages, cloud services, and distributed computing technologies. Evaluate emerging technologies and establish architectural patterns that improve scalability, reliability, security, and engineering productivity. Provide technical leadership through architecture reviews, mentoring, technical guidance, and engineering best practices. Partner with engineering, product, network, and business stakeholders to design solutions for complex technical and business challenges. Drive innovation through practical application of emerging AI technologies, intelligent automation, and modern software engineering practices. Produce clear technical documentation, architecture designs, and implementation guidance that support long-term platform evolution. Remain an active, hands-on engineer, contributing to software design, implementation, technical problem solving, and code reviews. Education and Work Experience: Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline with 7+ years of relevant experience, or an advanced degree with 5+ years of relevant experience. 7 – 10 years of technical engineering experience. Required Knowledge, Skills and Abilities Analytical Thinking Analytics Cloud Architectures Cloud Computing Collaboration Communication Customer Service Leadership Software Development Technical Evaluation Technical Planning Technical Writing Java Python RAG architectures Agentic AI design and development AI/LLM evaluation frameworks Azure AI Search LangChain, LangGraph Preferred Qualifications Demonstrated experience designing and delivering enterprise-scale software systems. Strong software engineering background with experience building scalable, distributed applications. Experience architecting cloud-native applications and distributed platforms. Proficiency in Java and Python. Experience applying modern AI technologies, including Generative AI and Large Language Models, within production software solutions. Strong analytical, problem-solving, and technical communication skills. Demonstrated ability to influence technical direction across engineering teams. Experience mentoring engineers and providing technical leadership. Experience working with large-scale data platforms, AI-powered applications, analytics platforms, or network data environments is highly desirable. Technology Environment You'll have the opportunity to work with technologies including: Artificial Intelligence Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Agentic AI Azure OpenAI Azure AI Search LangChain LangGraph Software Engineering Java Python Distributed Systems Cloud-Native Application Development Microservices Architecture Cloud & Data Microsoft Azure Databricks Snowflake Enterprise Data Platforms Large-Scale Data Processing Success in This Role Successful Principal Engineers: Deliver enterprise-scale AI, software, and data platforms that provide measurable business value. Solve complex technical challenges through sound architecture and engineering excellence. Build reusable platform capabilities that accelerate AI adoption and engineering productivity. Influence technical direction through collaboration, innovation, and technical leadership. Balance strategic thinking with hands-on software engineering. Mentor engineers while fostering a culture of innovation, continuous learning, and technical excellence. Continuously evaluate emerging technologies and identify practical opportunities to improve products, platforms, and engineering effectiveness. Why Join the Team This is an opportunity to help shape the future of AI-powered software and data platforms supporting one of the largest and most advanced telecommunications networks in the world. Licenses and Certifications: Certified Artificial Intelligence Professional (CAIP): Certification that validates expertise in designing and implementing AI solutions, including AI modeling and system integration. (Preferred) Project Management Professional (PMP) Internationally recognized certification that demonstrates proficiency in project management, crucial for overseeing AI integration projects. (Preferred) Certified Data Scientist (CDS): Certification that endorses skills in data science, crucial for the development and tuning of AI models. (Preferred) At least 18 years of age Legally authorized to work in the United States Travel: Travel Required (Yes/No): No DOT Regulated: DOT Regulated Position (Yes/No): No Safety Sensitive Position (Yes/No): No Base Pay Range: $150,700 - $271,900Corporate Bonus Target: 20% The pay range above is the general base pay range for a successful candidate in the role. The successful candidate's actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary