Sr Engineer, Commercial AI Forward Deployment

T-Mobile•Frisco, TX

3d•$142,300 - $256,700•Hybrid

About The Position

The Senior Engineer, Commercial AI Forward Deployment is an expert technical practitioner who embeds inside a T-Mobile business unit and operates with significantly greater autonomy than an Engineer FDE. Senior FDEs are the primary execution force: driving the technical agenda for net-new agentic AI delivery, mentoring Engineers co-deployed alongside them, and stepping in as acting domain lead when needed. This role bridges deep hands-on engineering with emerging leadership accountability. Performance is measured on validated ROI outcomes for the domain and on the quality and impact of the delivery team supported. This role reports to the Manager or Sr Manager, Forward Deployment Engineer within the assigned domain.

Requirements

Bachelor's Degree Computer Science, Software Engineering, Data Science, or related technical field. Relevant equivalent experience accepted.
4-7 years Production engineering experience with demonstrated hands-on LLM deployment: prompt engineering, RAG architecture, agent orchestration.
Proven ability to operate autonomously in ambiguous environments and deliver measurable AI outcomes.
Python Engineering: Strong production Python; proficiency in at least one additional language (Go, TypeScript, or Java). Architects robust agentic system components and writes code others can extend.
LLM System Design: Demonstrated hands-on experience deploying LLM-based systems: prompt engineering, RAG architecture, agent orchestration, hallucination mitigation, and performance benchmarking.
Data Engineering & Integration: Proficiency in complex SQL, ETL/ELT pipeline design, and experience building system integrations connecting AI solutions to enterprise and telecom data sources.
Cloud-Native Deployment: Docker, Kubernetes, CI/CD, and infrastructure experience on AWS (primary) or Azure/GCP; able to instrument deployed systems with real-time logging and feedback collection.
Technical Leadership Without Authority: Confirmed ability to lead technical delivery and mentor engineers in ambiguous environments; adapts communication to BU stakeholders and leadership alike.
Responsible AI & Data Security: Applies data privacy, security, and responsible AI principles in all system design and deployment decisions. Builds guardrails and compliance considerations into agentic solutions. Understands T-Mobile's data classification standards and handles critical data appropriately.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience building system integrations with enterprise data sources.
7-10 years Prior experience in solutions engineering, embedded technical, or forward deployment role.
Track record of delivering AI solutions that measurably improved a business outcome metric.
Experience navigating stakeholder environments from BU operators to middle management.

Responsibilities

Technical Domain Leadership: Drive the technical agenda for net-new agentic AI delivery within the assigned business domain. Lead scoping and diagnostic sessions with BU stakeholders and TPMs to define requirements, map workflows, and assess data and integration readiness. Maintain trusted working relationships with BU managers and communicate delivery progress and milestones to domain stakeholders.
Agentic System Delivery & Iteration: Design and deliver net-new agentic AI solutions in live production environments. Implement system integrations, RAG pipelines, prompt orchestration layers, and multi-agent workflows tailored to BU-specific needs. Run controlled A/B experiments and document measured ROI impact.
System Integration & Data Engineering: Build integration layers connecting AI solutions to BU tools and data sources. Normalize BU-specific datasets for AI system consumption. Identify and close data quality gaps and feed domain-specific insights back to the practice through structured engineering handoffs.
FDE Team Mentoring: Mentor and technically guide Engineers co-deployed in the same domain. Provide code review, solution iteration feedback, and coaching on delivery standards. Support onboarding of new FDEs rotating into the domain and contribute to FDE practice methodology.
Practice Reporting & Contribution: Contribute to practice reporting cycles that support TPM-defined requirements and delivery planning. Document failure modes, edge cases, and performance gaps in a structured format. Participate in rotation planning and knowledge transfer sessions.