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Senior Forward Deployment Engineer
T-MobileSenior Engineer, Forward Deployment at T-Mobile delivering AI solutions and mentoring engineering teams in fast-paced environments with strong emphasis on collaboration and innovation.
Posted 7/25/2026full-timeBellevue • Texas, Washington • 🇺🇸 United StatesSenior💰 $142,300 - $256,700 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in deploying LLM-based systems, including prompt engineering and RAG architecture, while ensuring data security and responsible AI principles. Proven ability to integrate AI solutions with enterprise data sources and deliver measurable business outcomes through effective stakeholder communication.
Highest-signal resume keywords
LLM System DesignPython EngineeringData Engineering & IntegrationCloud-Native DeploymentResponsible AI & Data Security
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Prompt EngineeringRAG ArchitectureAgent OrchestrationComplex SQLETL/ELT Pipeline DesignDockerKubernetesCI/CDAWSPerformance Benchmarking
Soft Skills
Stakeholder TranslationMentoringCommunicationAutonomous OperationBuilding Trust
Tools & Technologies
AI SolutionsIntegration LayersData SourcesReal-Time LoggingFeedback Collection
Certifications & Qualifications
Bachelor's Degree in Computer ScienceSoftware EngineeringData Science
Industry Keywords
Agentic AIProduction EngineeringSolutions EngineeringForward DeploymentData Quality
Tech Stack
Tools & technologiesAWSAzureCloudDockerETLGoGoogle Cloud PlatformJavaKubernetesPythonSQLTypeScript
About the role
Key responsibilities & impact- Drive the technical agenda for net-new agentic AI delivery within the assigned business domain
- Lead scoping and diagnostic sessions with BU stakeholders and TPMs to define requirements, map workflows, and assess data and integration readiness
- Maintain trusted working relationships with BU managers and communicate delivery progress and milestones to domain stakeholders
- Design and deliver net-new agentic AI solutions in live production environments
- Implement system integrations, RAG pipelines, prompt orchestration layers, and multi-agent workflows tailored to BU-specific needs
- Run controlled A/B experiments and document measured return on investment impact
- Build integration layers connecting AI solutions to BU tools and data sources
- Normalize BU-specific datasets for AI system consumption
- Identify and close data quality gaps and feed domain-specific insights back to the practice through structured engineering handoffs
- Mentor and technically guide Engineers co-deployed in the same domain
- Provide code review, solution iteration feedback, and coaching on delivery standards
- Support onboarding of new FDEs rotating into the domain and contribute to FDE practice methodology
- Contribute to practice reporting cycles that support TPM-defined requirements and delivery planning
- Document failure modes, edge cases, and performance gaps in a structured format
- Participate in rotation planning and knowledge transfer sessions
Requirements
What you’ll need- Bachelor's Degree Computer Science, Software Engineering, Data Science, or related technical field
- 4-7+ years production engineering experience with demonstrated hands-on LLM deployment: prompt engineering, RAG architecture, agent orchestration
- Validated ability to operate autonomously in ambiguous environments and deliver measurable AI outcomes
- Experience building system integrations with enterprise data sources
- 7-10+ years prior experience in solutions engineering, embedded technical, or forward deployment role
- Track record of delivering AI solutions that measurably improved a business outcome metric
- Experience navigating stakeholder environments from BU operators to middle management
- Python Engineering: Strong production Python; proficiency in at least one additional language (Go, TypeScript, or Java)
- LLM System Design: Demonstrated hands-on experience deploying LLM-based systems: prompt engineering, RAG architecture, agent orchestration, hallucination mitigation, and performance benchmarking
- Data Engineering & Integration: Proficiency in complex SQL, ETL/ELT pipeline design, and experience building system integrations connecting AI solutions to enterprise and telecom data sources
- Cloud-Native Deployment: Docker, Kubernetes, CI/CD, and infrastructure experience on AWS (primary) or Azure/GCP; able to instrument deployed systems with real-time logging and feedback collection
- Responsible AI & Data Security: Applies data privacy, security, and responsible AI principles in all system design and deployment decisions
- Forward Deployment Mentality: Demonstrated ability to embed within a business unit, earn partner trust rapidly and deliver working AI systems under real operational constraints
- Stakeholder Translation: Ability to move fluidly between technical implementation and business communication
Benefits
Comp & perks- 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
- 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
- voluntary long-term care insurance
- mobile service & home internet discounts
- pet insurance
- access to commuter and transit programs