Sr. AI Engineer

T-Mobile•Frisco, TX

2d•$133,100 - $240,100•Remote

About The Position

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 redefine the future of customer service with the power of AI? We’re looking for a Sr. AI Engineer to lead the evolution of T-Mobile’s Agentic Next Best Action (ANBA) capabilities—powering intelligent, real-time decisioning and enabling the next best customer experiences at scale. In this role, you will design and optimize agentic AI systems that determine and execute the most effective next action for each customer interaction, while shaping seamless, personalized experiences. Leveraging techniques such as prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and tool-integrated reasoning, you’ll build AI that dynamically orchestrates workflows, invokes APIs, and adapts decisions based on context and intent. You’ll work across engineering, product, and business teams to embed ANBA-driven intelligence into production systems—delivering proactive, outcome-oriented experiences that improve customer satisfaction and business results. This role is critical to advancing T-Mobile’s AI capabilities from traditional automation to autonomous, decision-driven systems that continuously learn and optimize both actions and experiences. We pride ourselves on encouraging a culture of innovation, advocating for agile methodologies, and promoting clarity in all that we do. Join us in embodying the spirit of the 'Un-carrier' and make a tangible impact! If you are passionate about driving excellence and want to make a significant impact, apply today!

Requirements

API Development – Python, REST APIs, OpenAPI/Swagger
Cloud Computing – AWS, Azure
Collaboration
Data Analysis
Data Management
Data Modeling
Prompt Engineering – OpenAI APIs, Hugging Face, Anthropic Claude, Google Gemini
Operational excellence practices and observability tools - Weights & Biases, Splunk, Datadog
Project management tools and agile methodologies - Jira, Azure DevOps
AI orchestration tools - LangChain, LlamaIndex, vector databases for retrieval augmented generation.
Bachelor's degree and 3+ years of related professional experience.
Master's degree (or higher) and 1+ year of related professional experience.
Equivalent combination of education, training, certifications, and professional experience.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Minimum 4 years professional experience in developing and optimizing AI models for customer service automation using advanced techniques such as prompt engineering and fine-tuning.
Minimum 4 years professional experience in architecting and deploying sophisticated agentic AI systems to enhance reasoning and interaction capabilities in complex workflows.
Minimum 4 years professional experience in collaborating with cross-functional teams to integrate AI-driven enhancements into production systems.
Certified Analytics Professional (CAP): Certification that endorses an individual's expertise in analytics, including the ability to transform complex data into valuable insights and actions, which is crucial for optimizing AI models in customer service automation.
NVIDIA Deep Learning AI Certification: This certification demonstrates proficiency in designing and deploying deep learning AI applications, relevant for enhancing AI model performance in complex systems like customer service workflows.
Certified Data Scientist (CDS): Certification that validates the skills required to analyze data scientifically and use it for operational improvements, which supports the development and optimization of AI tools and workflows.

Responsibilities

Optimize AI performance through prompt engineering and fine-tuning to enhance customer service automation.
Develop AI tools and workflows to support implementation of advanced AI systems within customer service operations.
Proficiency in Python and AI development frameworks for building scalable AI applications.
Architect sophisticated agentic AI systems to improve reasoning and interaction capabilities across complex workflows.
Collaborate with cross-functional teams to ensure seamless integration of AI-driven enhancements into production systems.
Evaluate the reliability, accuracy, and efficiency of AI models to ensure alignment with strategic objectives and customer satisfaction.
Conduct ongoing research to stay updated with the latest AI technologies and methodologies applicable to customer service.