Principal Engineer, Commercial AI Forward Deployment

T-Mobile•Frisco, TX

3d•$164,500 - $296,700•Hybrid

About The Position

The Principal Engineer, Commercial AI Forward Deployment is T-Mobile's senior IC AI delivery leader on the FDE team. This role owns the end-to-end delivery of net-new agentic AI solutions within an assigned business domain from initial scoping through production optimization. Working within requirements defined by TPMs and BU stakeholders, the Principal FDE independently owns the domain relationship, sets the technical agenda for the FDE team in the domain, and mentors FDEs working alongside them. Leading without formal authority, this role builds trust with BU operations leaders and translates business requirements into agentic AI solutions in days, not quarters. Performance is evaluated exclusively on validated ROI targets for each domain assignment, not on activity, tickets, or deployments shipped. This role reports to the Sr Manager or Sr Director, Agentic Automation & FDE.

Requirements

Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related technical field.
7-10 years Production engineering experience including 3+ years delivering LLM-based agentic systems: prompt engineering, RAG architecture, agent orchestration, system integrations.
Track record of delivering AI solutions that measurably improved a business outcome metric in production.
Demonstrated ability to work within TPM-driven requirements processes and translate business needs into technical delivery.
Python Engineering: 7+ years production Python (required), plus proficiency in at least one of Go, TypeScript, or Java.
LLM System Architecture: Demonstrated hands-on expertise designing and deploying LLM-based production systems: prompt engineering, RAG architecture, agent orchestration, performance benchmarking, and hallucination mitigation at scale.
Data Engineering & System Integration: Proficiency in complex SQL, ETL/ELT pipeline design, and architecture of system integrations connecting AI solutions to enterprise data sources at scale.
Cloud-Native Deployment & MLOps: Docker, Kubernetes, CI/CD, infrastructure on AWS (primary) or Azure/GCP; vector database experience; MLOps: model versioning, A/B testing, monitoring, and observability.
Stakeholder Leadership: Proven ability to lead technical delivery in ambiguous environments without formal authority. Adapts communication to frontline operators, middle management, and C-suite. Comfortable operating across enterprise business domains.
Responsible AI & Data Governance: Designs and implements guardrails, security controls, and responsible AI review processes for all agentic solutions. Ensures compliance with T-Mobile's data privacy standards including CPNI and PII requirements. Serves as technical accountability point for AI safety and compliance within the domain.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Master's Degree preferred; relevant equivalent experience accepted.
More than 10 years Prior experience in a solutions engineering, forward deployment, or embedded technical role at a high-growth AI or cloud company.
Experience navigating complex stakeholder environments from frontline operators through C-suite.
Background in enterprise technology adoption or change management.

Responsibilities

Domain Ownership & BU Relationship: Full lifecycle ownership of net-new agentic AI delivery within the assigned domain from initial scoping through production optimization. Partner with TPMs and BU stakeholders to define requirements, map real workflows, and assess data and integration readiness. Build and maintain trust with BU operations leaders, managers, and end users. Present domain ROI outcomes and delivery roadmap to BU leadership quarterly.
Agentic System Delivery & Iteration: Design and deliver net-new agentic AI solutions in live production environments. Architect and implement system integrations, RAG pipelines, prompt orchestration, and multi-agent workflows tailored to BU-specific needs. Run controlled A/B experiments in production cohorts to measure and document validated ROI impact. Instrument deployed systems with real-time logging and feedback collection for continuous improvement.
System Integration & Data Engineering: Build and own integration layers connecting AI solutions to BU tools and data sources (CRM, billing, inventory, contract repositories). Normalize BU-specific datasets for AI system consumption. Identify and close data quality gaps that limit solution accuracy or reliability. Feed domain-specific insights back into the practice through structured engineering handoffs.
FDE Practice Leadership: Mentor and technically guide FDEs co-deployed in the domain or adjacent domains. Contribute to FDE practice standards including engagement methodology, diagnostic frameworks, responsible AI review processes, and data security guidelines. File bi-weekly reports documenting failure modes, edge cases, and performance gaps. Participate in rotation planning and knowledge transfer for incoming FDEs.
Strategic AI Delivery & Responsible AI: Serve as the technical accountability point for AI safety, data privacy, and responsible AI compliance within the domain. Ensure all delivered solutions meet T-Mobile's data governance and security standards, including CPNI and PII requirements. Partner with TPMs and practice leadership to translate domain delivery learnings into practice improvements. Represent FDE validated ROI outcomes in cross-functional senior leadership forums.