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T-Mobile

Connects U.S. customers by phone and internet

Forward Deployment Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field is required; relevant equivalent experience is accepted.
  • Two to four or more years of hands-on software or machine learning engineering experience in production environments, including writing clean, maintainable Python code and debugging and extending existing codebases.
  • Experience deploying to cloud environments and building system integrations with enterprise data sources.
  • Python proficiency in production settings, including the ability to read, debug, and extend existing agentic-system code written by others.
  • Working knowledge of large language model integration patterns, including prompt engineering, retrieval-augmented generation basics, and function calling, plus experience with at least one major large language model provider.
  • SQL proficiency; experience building integrations between AI solutions and enterprise data sources such as customer relationship management, ticketing, enterprise resource planning, and billing systems; ability to build lightweight extract-transform-load or extract-load-transform pipelines and instrument systems with basic logging.
  • Comfort deploying to Amazon Web Services or Microsoft Azure, using Docker, and reading continuous integration and continuous delivery pipelines.
  • Understanding of enterprise data privacy requirements, including personally identifiable information and customer data protection, and application of responsible AI principles and appropriate data handling practices.
  • Ability to embed within a business unit, earn stakeholder trust rapidly, and deliver working AI systems under operational constraints.
  • Ability to translate technical trade-offs into plain-language impact narratives for business-unit managers and convert vague business requests into precise engineering requirements.
  • Experience compressing the gap between proof of concept and production-grade delivery.
  • Must be at least 18 years of age.
  • Must be legally authorized to work in the United States.

Responsibilities

  • Implement, configure, and iteratively tune new agentic AI solutions in the assigned business domain according to requirements defined and delivered by technical program managers; adapt solution behavior, prompt layers, and escalation logic using live operational feedback on a weekly cycle.
  • Run controlled A/B experiments in live production cohorts, document measured impact against validated return-on-investment targets, and share structured analysis with the forward deployment team and practice leadership to inform delivery prioritization.
  • Work alongside business-unit teams in care, retail, finance, supply chain, or other operational contexts; observe workflows, identify friction AI solutions can address, and conduct structured feedback sessions with business-unit managers and end users.
  • Build integrations connecting AI solutions to business-unit data sources such as customer relationship management, billing, ticketing, and enterprise resource planning platforms; prepare and normalize business-unit data for AI consumption.
  • Build lightweight extract-transform-load pipelines that feed operational data into evaluation loops and monitoring dashboards; document and escalate data-quality gaps.
  • Contribute to reporting cycles supporting the technical-program-manager-defined requirements pipeline; document system performance, failure modes, and gaps in a structured format for domain planning and delivery prioritization; participate in practice reviews and share domain learnings.
  • Document failure modes, edge cases, and performance gaps for practice reporting cycles.
  • Participate in rotation planning and knowledge-transfer sessions and contribute to peer knowledge sharing.
  • Support onboarding of rotating forward deployment engineers at the individual-contributor level.
  • Implement integrations and data-normalization pipelines for assigned business-unit data sources, and flag data-quality issues to the senior forward deployment engineer or technical program manager.
  • Build and iterate on assigned components of agentic systems, individual agents, retrieval-augmented generation pipelines, and prompt layers under architectural direction.
  • Deliver A/B experiments and document the results.

Desired Qualifications

  • Four to seven or more years of prior experience in a customer-facing, operations, or embedded technical role in care, retail, finance, or supply chain.
  • Exposure to enterprise AI platforms such as Salesforce Einstein, ServiceNow AI, or Microsoft Copilot.

About the Company

T-Mobile

Connects U.S. customers by phone and internet

T-Mobile runs a nationwide wireless network for consumers and businesses in the United States, selling mobile phone service and broadband internet access. Its flagship T-Mobile brand sits alongside prepaid brands Metro by T-Mobile and Mint Mobile, reaching customers with different budgets and payment preferences. Customers connect through phones or home internet gateways, while businesses buy connectivity for staff and connected equipment. Revenue comes from recurring service plans, wholesale network access, and sales of devices and accessories. Its operating roots date to 1994, and its headquarters are in Bellevue, Washington, and Overland Park, Kansas.

Company size
10,001+
Company stage
IPO
Headquarters
Bellevue, WA
Founded
1994

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