This role pays more than
60%
of similar roles. Most pay
$149,500–$219,362
— the shaded band above.
At the midpoint, this role pays about
$200k
versus about
$184k
for comparable roles.
Based on 240 similar postings.
Employer
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
21 open roles
on FindRole.
Listed pay typically runs
$127,800–$214,360
across 21 roles with salary data.
Sr Forward Deployment Engineer
The Sr Forward Deployment Engineer serves as a technical leader within a specific business unit, driving the technical agenda for net-new agentic AI delivery. This role involves designing and delivering agentic AI solutions in production environments, including RAG pipelines, prompt orchestration layers, and multi-agent workflows. The engineer is responsible for building integration layers to connect AI systems with enterprise data sources, performing data normalization, and conducting A/B experiments to measure return on investment. Key responsibilities include mentoring co-deployed engineers, managing stakeholder relationships, and overseeing end-to-end solution architecture. Required skills include production Python, proficiency in Go, TypeScript, or Java, and expertise in SQL, ETL/ELT pipelines, and cloud-native technologies like Docker, Kubernetes, and AWS. The role focuses on solving complex integration challenges by bridging the gap between technical implementation and business requirements for agentic systems.
Drive the technical agenda for net-new agentic AI delivery within assigned business domains.
Design and deploy agentic AI solutions including RAG pipelines, prompt orchestration, and multi-agent workflows in production environments.
Build integration layers to connect AI solutions with enterprise data sources and tools.
Mentor and provide technical guidance, code reviews, and coaching to co-deployed engineers.
Lead scoping sessions with stakeholders to define requirements, map workflows, and assess data readiness.
Manage end-to-end solution architecture and make independent design decisions across the full agentic stack.
Communicate delivery progress, milestones, and ROI outcomes directly to business unit managers and stakeholders.
Author domain case studies and contribute to the development of internal engineering playbooks.
What we're looking for
Must have a Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
Must have 4-7+ years of production engineering experience with hands-on LLM deployment including prompt engineering, RAG architecture, and agent orchestration.
Preferred: 7-10+ years of experience in solutions engineering, embedded technical roles, or forward deployment roles.
Must possess strong production Python skills and proficiency in at least one other language such as Go, TypeScript, or Java.
Must have expertise in LLM system design, including hallucination mitigation and performance benchmarking.
Must be proficient in complex SQL, ETL/ELT pipeline design, and building integrations with enterprise data sources.
Must have experience with cloud-native deployment using Docker, Kubernetes, CI/CD, and infrastructure on AWS, Azure, or GCP.
Must be legally authorized to work in the United States and at least 18 years of age.