Forward Deployment Engineer

T-Mobile USA•Bellevue, WA

1d•$117,800 - $212,500

About The Position

The Forward Deployment Engineer is a hands-on technical practitioner who embeds within an assigned T-Mobile business unit to design, build, deploy, and iterate on new agentic AI solutions. The role executes against requirements defined and scoped by TPMs and business-unit stakeholders, typically working alongside a Senior Forward Deployment Engineer who owns the domain relationship and sets technical direction. The Engineer builds integrations, tunes prompts and escalation logic, runs experiments, debugs production systems, and delivers against validated return-on-investment targets. Performance is measured by contribution to validated ROI outcomes for each domain assignment. The position works directly with teams in operational domains such as care, retail, finance, and supply chain. It combines software and data engineering with production experimentation, stakeholder engagement, structured reporting, and knowledge sharing. The Engineer also participates in rotation planning and knowledge transfer and may support onboarding of rotating individual-contributor FDEs.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field, or relevant equivalent experience.
2–4+ years of hands-on software or ML engineering experience in production environments.
Ability to write clean, maintainable Python code and debug and extend existing codebases.
Experience deploying to cloud environments and building integrations with enterprise data sources.
Proficiency with Python in production settings, including reading, debugging, and extending existing agentic-system code.
Working knowledge of LLM integration patterns, including prompt engineering, RAG basics, and function calling, and experience with at least one major LLM provider.
SQL proficiency and experience building enterprise data integrations, lightweight ETL/ELT pipelines, and basic system logging.
Comfort deploying to AWS or Azure, using Docker, and reading CI/CD pipelines.
Ability to ship iterative improvements quickly and communicate technical trade-offs clearly to non-technical partners.
Understanding of enterprise data privacy requirements, including PII and customer-data protection, and ability to apply responsible AI and data-handling practices.
Ability to embed within a business unit, build stakeholder trust, and deliver working AI systems under real operational constraints.
Ability to translate engineering trade-offs into plain-language impact narratives and turn business requests into precise engineering requirements.
Experience compressing the gap between proof of concept and production-grade delivery.
At least 18 years of age.
Legally authorized to work in the United States.
Willingness to travel; travel is required.

Nice To Haves

4–7+ 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.

Responsibilities

Implement, configure, and iteratively tune agentic AI solutions for an assigned business domain against TPM-defined requirements.
Adapt solution behavior, prompt layers, and escalation logic based on live operational feedback.
Run controlled A/B experiments in production cohorts, document measured impact against validated ROI targets, and share structured analysis with the FDE team and practice leadership.
Work alongside business-unit teams, observe workflows, identify opportunities for AI solutions, and conduct structured feedback sessions with managers and end users.
Build integrations between AI solutions and business-unit data sources such as CRM, billing, ticketing, and ERP platforms.
Prepare and normalize business-unit data for AI system consumption and build lightweight ETL pipelines for evaluation loops and monitoring dashboards.
Identify and document data-quality gaps and escalate them to a Senior FDE or TPM.
Document system performance, failure modes, edge cases, and gaps to support reporting, domain planning, and delivery prioritization.
Participate in practice reviews, rotation planning, knowledge-transfer sessions, and peer knowledge sharing.
Support onboarding of rotating FDEs at the individual-contributor level.
Build and iterate on assigned agentic-system components, including individual agents, RAG pipelines, and prompt layers, under architectural direction.

Benefits

Competitive base salary and compensation package, including an annual incentive opportunity for eligible roles.
Annual stock grant and employee stock purchase plan.
401(k).
Access to free, year-round money coaches.
Medical, dental, and vision insurance.
Flexible spending account.
Paid time off and up to 12 paid holidays.
Paid parental and family leave.
Family-building benefits, backup care, enhanced family support, and childcare subsidy.
Tuition assistance and college coaching.
Short- and long-term disability coverage.
Voluntary AD&D, accident, life, disability, and long-term care coverage.
Mobile service and home internet discounts for eligible employees.
Pet insurance for eligible employees.
Commuter and transit programs for eligible employees.