Forward Deployment Engineer

About the role

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.

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.
• 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 the domain.
• BU Partnership & Workflow Engagement: Work directly alongside BU teams in the assigned domain across care, retail, finance, supply chain, or other operational contexts.
• Data Engineering & System Integrations: Build system integrations connecting AI solutions to BU data sources such as CRM, billing, ticketing, and ERP platforms.
• Practice Reporting & Requirements Support: Contribute to reporting cycles that support the TPM-defined requirements pipeline.
• Contributes structured documentation: failure modes, edge cases, performance gaps, and develops them into practice reporting cycles.
• Participates in rotation planning and knowledge transfer sessions.
• Contributes to peer knowledge sharing
• Supports onboarding of rotating FDEs at the IC level.
• Implements integrations and data normalization pipelines for assigned BU data sources.
• Flags data quality issues and raises to Sr. FDE or TPM.
• Builds and iterates on assigned components of agentic systems, individual agents, RAG pipelines, prompt layers, while under architectural direction.
• Delivers A/B experiments and documents results.

Qualifications

Bachelor's Degree Computer Science, Software Engineering, Data Science, or related technical field. Relevant equivalent experience accepted.

2-4+ years hands-on software or ML engineering experience in production environments. Demonstrated ability to write clean, maintainable Python code and to debug and extend existing codebases.

4-7+ years prior experience in a customer-facing, operations, or embedded technical role (care, retail, finance, supply chain). Exposure to enterprise AI platforms such as Salesforce Einstein, ServiceNow AI, or Microsoft Copilot.

Skills

• Python Engineering: Python proficiency in production settings: clean, maintainable code; able to read, debug, and extend existing agentic system code written by others.
• LLM Integration: Working knowledge of LLM integration patterns: prompt engineering, RAG basics, function calling; experience with at least one major LLM provider.
• Data Engineering & System Integrations: SQL proficiency; experience building system integrations connecting AI solutions to enterprise data sources (CRM, ticketing, ERP, billing); able to build lightweight ETL/ELT pipelines and instrument systems with basic logging.
• Cloud & DevOps Literacy: Comfortable deploying to AWS or Azure, using Docker, and reading CI/CD pipelines.
• Operational Bias to Action: Ships iterative improvements in days, not weeks; able to communicate technical trade-offs clearly to non-technical partners.
• Data Security & Responsible AI: Solid understanding of data privacy requirements in enterprise environments including PII and customer data protection.
• Forward Deployment Mentality: Demonstrated ability to embed within a business unit, earn stakeholder trust rapidly, and deliver working AI systems under real operational constraints, not in sandbox or lab environments.
• Stakeholder Translation: Ability to move fluidly between technical implementation and business communication, converting engineering tradeoffs into plain-language impact narratives for BU managers, and converting vague business asks into precise engineering requirements.
• Rapid Prototyping & Production Readiness: Experience compressing the gap between proof-of-concept and production-grade delivery.

Benefits

Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance.

Pay

Base Pay Range: $117,800 - $212,500. Corporate Bonus Target: 15%. The pay range above is the general base pay range for a successful candidate in the role. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.