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NEXTMOVEFDE careers · United States
T-Mobile

Forward Deployment Engineer

AI summary of the role

Hands-on engineer embedded in a T-Mobile business unit to design, build, and tune net-new agentic AI solutions.

What you’ll do

  • Implement, configure, and iteratively tune net-new agentic AI solutions in an assigned business domain.
  • Run controlled A/B experiments in live production cohorts and document impact on validated ROI targets.
  • Build system integrations connecting AI solutions to enterprise data sources (CRM, billing, ticketing, ERP).
  • Work directly with business unit teams to observe workflows and conduct structured feedback sessions.

What you’ll bring

  • Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related field (or equivalent experience).
  • 2-4+ years hands-on software or ML engineering experience in production environments.
  • Proficiency in Python for production settings.
  • Working knowledge of LLM integration patterns (prompt engineering, RAG, function calling).

Technologies

Python · LLM · RAG · prompt engineering · function calling · SQL · ETL · CRM · ERP · Salesforce Einstein · ServiceNow AI · Microsoft Copilot

About T-Mobile

Third-largest US wireless carrier ('Un-carrier'), serving 100M+ customers with 5G mobile, home internet, and a fast-growing fiber broadband footprint.

Public · 5000+ people

Source and classification

Internal deployment & tooling · Evidence for this classification:

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees! Are you ready to join the Un-carrier movement? The Engineer, Forward Deployment is a hands-on technical practitioner who embeds within a T-Mobile business unit to design, build, and iterate on net-new agentic AI solutions. These solutions are developed against requirements defined and scoped by TPMs and business unit stakeholders. Forward Deployment Engineers (FDEs) write code, run experiments, debug production systems, and work closely with
More from the job description

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees! Are you ready to join the Un-carrier movement? The Engineer, Forward Deployment is a hands-on technical practitioner who embeds within a T-Mobile business unit to design, build, and iterate on net-new agentic AI solutions. These solutions are developed against requirements defined and scoped by TPMs and business unit stakeholders. Forward Deployment Engineers (FDEs) write code, run experiments, debug production systems, and work closely with business unit stakeholder teams to deliver AI solutions that achieve stated business outcomes. FDEs typically work alongside a Senior FDE who owns the domain relationship and sets technical direction. The Engineer is responsible for the execution layer: building system integrations, tuning prompts, running A/B cohorts, and delivering against validated ROI targets for the domain. Performance is measured by contribution to validated return on investment outcomes for each domain assignment — not by activ [... source excerpt omitted ...] ies, and promoting transparency in all that we do. Join us in embodying the spirit of the 'Un-carrier' and make a tangible impact! If you're up to the challenge, apply today! Job Responsibilities: AI System Deployment & Tuning: Implement, configure, and iteratively tune net-new agentic AI solutions deployed in the assigned business domain, working against requirements defined and delivered by TPMs. Adapt solution behavior, prompt layers, and escalation logic based on live operational feedback on a weekly cycle. A/B Experimentation & ROI Validation: Run controlled A/B experiments in live production cohorts and document measured impact on validated return on investment targets for th [... source excerpt omitted ...] ETL pipelines feeding operational data into evaluation loops and monitoring dashboards. Identify and escalate data quality gaps with specific documentation. Practice Reporting & Requirements Support: Contribute to reporting cycles that support the TPM-defined requirements pipeline. Document system performance, failure modes, and gaps in a structured format that supports domain planning and delivery prioritization. Participate in practice reviews to share domain learnings. Contributes structured documentation: failure modes, edge cases, performance gaps, and develops them into practice reporting cycles. Participates in rotation planning and knowledge transfer sessions. Contribute

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