Principal Engineer, Commercial AI Forward Deployment

T-Mobile

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Frisco, TXBellevue, WA
Employment
Full-time
Posted
11 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $209k
$133k $278k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $172,375–$245,762.

Based on 240 similar postings.

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About T-Mobile

T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications

T-Mobile currently has 71 open roles on FindRole.

Listed pay typically runs $135,700–$230,700 across 31 roles with salary data.

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At a glance

TL;DR · Principal Engineer, Commercial AI Forward Deployment

The Principal Engineer, Commercial AI Forward Deployment serves as the senior technical lead for complex commercial AI engagements, supporting Kinetic Edge AI and broader Physical AI programs. This role involves embedding with customer teams to transform ambiguous use cases in smart cities, public safety, and industrial automation into working systems using network edge compute and cloud infrastructure. You will write and ship production code for multi-sensor fusion, real-time edge inference, and data-at-scale layers including ingestion, fine-tuning, and training. Key technologies include Kubernetes, OpenShift, 5G network slicing, and frameworks like ROS 2, NVIDIA Isaac, or DeepStream. You will provide technical leadership, define production-readiness criteria, and manage the technical direction for sensor and vision data while ensuring solutions align with RF propagation physics and GPU capacity.

What you'll do

  • Serve as the lead technical engineer for complex commercial AI engagements and customer deployments.
  • Write and ship production code for multi-sensor fusion, real-time edge inference, and network integration.
  • Own the technical direction for sensor and vision data-at-scale layers including ingestion and training.
  • Make build decisions across workstreams to align solution designs with network and edge compute capabilities.
  • Communicate technical tradeoffs and project feasibility to customer executives in plain language.
  • Define production-readiness criteria and lead root cause analysis for major deployment incidents.
  • Identify and select field-built components to graduate into the core product platform.
  • Provide technical leadership by reviewing critical code and directing the work of senior engineers.

What we're looking for

  • Bachelor's Degree and 7 years of related work experience OR an equivalent combination of education and experience.
  • Production software development and code review skills.
  • Data and ML pipeline engineering experience including ingestion, fusion, fine-tuning, training, and inference.
  • Experience with edge and real-time inference systems.
  • Experience with containerized and edge deployment using Kubernetes or OpenShift.
  • Ability to provide technical leadership without formal authority and communicate technically with executives.
  • 7-10 years of professional software or systems engineering experience, including customer-facing or forward-deployed work (preferred).
  • Authorized to work in the United States.

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