Principal Engineer, Commercial AI Forward Deployment

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. ** This is not a remote position. T-Mobile is a hybrid work environment requiring work in the office three (3) days per week. The successful candidate will be located in either Seattle, Washington or Frisco, Texas areas.** Total Rewards 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 Principal Engineer, Commercial AI Forward Deployment is the senior technical engineer on T-Mobile's most complex commercial AI engagements and often the first technical point of contact a strategic customer works with. The role supports T-Mobile's commercial AI programs. Responsibilities include supporting Kinetic Edge AI (KEAI) and the broader Physical AI program, but are not limited to them, and will extend to AI applications T-Mobile sells to business customers. This person embeds with customer teams to turn ambiguous, often unprecedented use cases in areas such as smart city and public safety, utilities, industrial automation, and autonomous mobility into working systems on T-Mobile's network, edge compute, and cloud. They are equally comfortable writing an inference pipeline for a robotics workload, explaining network slicing to a customer executive, and telling a business team when a timeline does not fit the physics of RF propagation or the GPU capacity available. This is a build-and-lead role, not an advisory one. The Principal Engineer writes and ships production code on the hardest problems, owns technical direction for the sensor and vision data-at-scale layer (ingestion, fusion, fine-tuning, training) on their engagements, and sets the engineering standards other FDEs follow. They decide with AI Engineering which field-built components are ready to graduate into the platform. Success is measured by working deployments on the most complex engagements, production stability, and the amount of field work that becomes reusable platform capability. Job Responsibilities : Serve as the lead technical engineer on the most complex customer engagements, setting the technical approach where no industry playbook exists. Write and ship production code on the highest-risk parts of each engagement, such as multi-sensor fusion, real-time edge inference, device and network integration, and performance tuning. Own technical direction for the sensor and vision data-at-scale layer on assigned engagements, including ingestion, fusion, fine-tuning, and training, built to platform standards from day one so productization is a graduation, not a rewrite. Make build decisions that span workstreams and teams, partnering with the Principal Architect on solution design and with Network RAN and Core engineering on connectivity and edge compute. Keep customer and internal business commitments grounded in what the network, edge infrastructure, and current AI capabilities can deliver, and explain tradeoffs in plain language executives can act on. Define production-readiness criteria, evaluation methods, and operational standards for field deployments, and lead root cause analysis and post-mortems for major incidents. Decide with AI Engineering and product owners which field-built components graduate into the platform, and bring the product roadmap evidence drawn from multiple deployments. Provide technical leadership without formal authority: direct the technical work of Sr Engineers and Engineers, review critical code, and raise the hiring bar for the FDE team. Also responsible for other duties/projects as assigned by business management as needed. Required Education: 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, Computer Engineering, Electrical Engineering, Data Science, Telecom Engineering, Robotics, or a related field; Master's degree a plus Preferred Work Experience : 7-10 years of professional software or systems engineering, including customer-facing, solutions, or forward-deployed engineering work Demonstrated experience designing and delivering production or pilot systems involving IoT devices, cameras, sensors, robotics, drones, or autonomous systems Experience with data science, ML, or big data platforms (e.g., Databricks, Snowflake, or equivalent), including model fine-tuning and evaluation Working knowledge of cellular network fundamentals such as RAN architecture, network slicing, private networks, and SIM/eSIM provisioning Experience leading technical work across multiple engineers or teams on ambiguous, customer-facing programs Required Knowledge, Skills and Abilities : Production Software Development and Code #J-18808-Ljbffr tmobile