Principal Architect, Commercial AI FDE

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** 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.**

Job Overview
This is a forward-deployed principal architect who embeds directly with T-Mobile's B2B customers to design and build the end-to-end technical solution for the company's commercial AI products (Physical Edge AI and Data Products). The role translates real customer use cases into deployable architectures on T-Mobile's cellular network and edge platform, ISV ecosystem, and data-at-scale layer, carrying solutions from proof-of-concept through production. It blends deep solution architecture with hands-on delivery and direct customer engagement, making rapid technical trade-offs in the field rather than from a central function, and turning validated pilots into reusable reference architectures that scale across customers. Because these solutions are delivered over T-Mobile's network, deep working knowledge of cellular network and connectivity (5G, network slicing, and edge/MEC) is core to the role. It is distinguished from a central enterprise architect by its customer-embedded, build-oriented nature and its close partnership with the Product Management & AI Engineering, which productizes field learnings into the platform. Success is measured by validated customer pilots and the speed by which they are deployed, that convert to production and revenue.

Job Responsibilities

• Embed directly with B2B customers to design end-to-end solutions and build proofs-of-concept on T-Mobile's edge platform, ISV ecosystem, and data-at-scale layer (ingestion, fusion, fine-tuning, inference).
• Translate ambiguous customer use cases and requirements into deployable architectures that meet latency, accuracy, reliability, and cost targets.
• Make hands-on architectural and integration trade-offs in the field, iterating rapidly with customers and ISV partners.
• Build and integrate - prototype, wire up data/ML pipelines, and integrate third-party software; not solution design alone.
• Develop reusable reference architectures, integration patterns, and standards so proof-of-concept findings productize cleanly into the platform, partnering with AI Engineering.
• Serve as the primary technical point of contact across customer engagements, solution and PRD reviews, and the transition from pilot to production and revenue.
• Provide technical leadership and mentorship to forward-deployed engineers and deployment strategists on the engagement/POD teams.
• Also responsible for other duties/projects as assigned by business management as needed.

Education and Work Experience

Required:

• Bachelor's Degree and 7 years of related work experience OR a combination of education and experience deemed equivalent 
• Working knowledge of cellular network and connectivity - 5G, network slicing, edge/MEC, and SIM provisioning and how they shape edge-AI solution design 

Preferred:

• Acceptable areas of study include Computer Science, IT, Computer Engineering, Telecom Engineering or a related field 
• 7-10 years dynamic experience as a forward-deployed engineer, solutions architect, or delivery consultant embedding directly with external customers to design and build technical solutions
• Hands-on experience building and deploying solutions - prototyping, data/ML pipelines, containerized/edge deployment (OpenShift/Kubernetes), and integrating third-party/ISV software 
• Experience with edge computing, real-time inference, distributed systems, and AI/ML platforms; designing for latency, reliability, and cost at scale 
• Experience taking solutions from proof-of-concept through production with external customers 
• 2-4 years of supervisory or technical-leadership experience 

Knowledge, Skills and Abilities

Required:

• Cellular Network & Connectivity - 5G, network slicing, edge/MEC, SIM provisioning
• Solution Architecture & Design 
• Systems & Cloud Architecture 
• Hands-on Software / Prototype Development 
• Data & ML Pipeline Design (ingestion, fusion, fine-tuning, inference)
• Edge / Real-time Inference Architecture
• ISV