Forward Deployment Engineer

T-Mobile

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Bellevue, WAFrisco, TX
Salary
$135,470–$244,375 / yr
Employment
Full-time
Posted
7 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $188k
This role $190k
$122k $257k
below market most similar roles pay here above market

This role pays less than 58% of similar roles. Most pay $152,725–$222,500 — the blue band above. At the midpoint, this role pays about $190k versus about $188k 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 72 open roles on FindRole.

Listed pay typically runs $138,996–$228,650 across 32 roles with salary data.

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View all roles at T-Mobile

At a glance

TL;DR · Forward Deployment Engineer

The Forward Deployment Engineer joins a specialized team to design, build, and iterate on net-new agentic AI solutions embedded within specific business units. This role involves writing Python code, running experiments, and debugging production systems to deliver AI solutions that achieve validated business outcomes. Key responsibilities include building system integrations with CRM, billing, and ERP platforms, tuning prompts, and running A/B experiments in live production cohorts. The engineer must develop lightweight ETL pipelines, manage RAG pipelines, and ensure data normalization for AI consumption. Required skills include Python engineering, SQL proficiency, LLM integration patterns, and cloud literacy in AWS or Azure. The work focuses on solving operational friction in domains like care, retail, finance, and supply chain by converting vague business asks into precise engineering requirements.

What you'll do

  • Design, build, and iterate on net-new agentic AI solutions within assigned business units.
  • Implement and tune prompt layers, escalation logic, and AI system behaviors based on operational feedback.
  • Run controlled A/B experiments in production cohorts to validate return on investment targets.
  • Build system integrations and lightweight ETL pipelines connecting AI solutions to CRM, billing, and ERP data.
  • Normalize business-unit-specific data and identify data quality gaps for AI system consumption.
  • Observe real workflows to identify friction points and conduct feedback sessions with end users and managers.
  • Document system performance, failure modes, and edge cases to support domain planning and reporting.
  • Write clean, maintainable Python code to debug and extend existing production codebases.

What we're looking for

  • Bachelor's Degree in Computer Science, Software Engineering, Data Science, or a related technical field.
  • 2-4+ years of hands-on software or ML engineering experience in production environments.
  • Proficiency in writing, debugging, and extending clean Python code in production settings.
  • Working knowledge of LLM integration patterns including prompt engineering, RAG basics, and function calling.
  • SQL proficiency and experience building system integrations with enterprise data sources like CRM, billing, and ERP.
  • Experience deploying to AWS or Azure using Docker and reading CI/CD pipelines.
  • 4-7+ years of experience in customer-facing, operations, or embedded technical roles (preferred).
  • Authorized to work in the United States.

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