Sr. AI Engineer

T-Mobile•Frisco, TX

2d•Onsite

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

4+ yrs developing and deploying machine learning models, particularly in the context of AI-driven customer service automation.
4+ yrs experience with advanced AI techniques such as prompt engineering, fine-tuning, and creating AI tools and workflows
4+ collaborating with cross-functional teams to integrate AI systems into production environments
Proficiency in Python and AI development frameworks for building scalable AI applications.
Experience with operational excellence practices and observability tools (e.g., Weights & Biases, Splunk, Datadog) for monitoring, logging, and troubleshooting AI systems in production.
Experience with project management tools and agile methodologies (e.g., Jira, Azure DevOps) to plan, track, and deliver AI initiatives efficiently in cross-functional environments.
Experience in LLM fine-tuning and prompt engineering (e.g., OpenAI APIs, Hugging Face, Anthropic Claude, Google Gemini)
Experience with AI orchestration tools (e.g., LangChain, LlamaIndex, vector databases for retrieval augmented generation).
Hands-on knowledge of function calling and API-based reasoning models (e.g., using structured outputs to drive automated workflows).
Familiarity with RAG pipelines and vector database retrieval for augmenting AI responses.
Understanding of multi-agent architectures and best practices in agentic AI design.
Experience with real-world AI evaluation techniques, including golden sets, synthetic data generation, and interactive testing.
Ability to collaborate across teams, working with engineers, product managers, and conversational designers to refine AI-driven solutions.
Bachelor’s degree in computer science, AI, or equivalent experience (Required)
In lieu of degree, equivalent industry experience may be considered. (Required)
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Master's/Advanced Degree in Computer Science or Artificial Intelligence (Preferred)

Responsibilities

Builds agentic AI systems that accomplish complex tasks by invoking AI models as well as internal and third-party tools using APIs, ensuring seamless data flow in production environments
Optimizes performance of agentic AI systems through innovative techniques such as prompt engineering, fine-tuning and reinforcement learning using T-Mobile’s customer interaction data
Develops AI tools, workflows, and middleware to enhance model capabilities, such as structured reasoning, multi-step task execution, and improved contextual memory.
Implements retrieval-augmented generation (RAG) techniques to ensure AI responses are contextually accurate and grounded in real-time data.
Collaborates in a highly matrixed environment with backend engineers, business experts and conversation designers to ensure AI-driven enhancements are effectively integrated into production environments
Tracks success metrics that aligns with business requirements and continuously evaluate and improve model quality based on those metrics
Develops internal tooling and automation to streamline AI deployment, evaluation, and self-improvement mechanisms.
Monitors real-world AI performance and proactively iterates on model behavior based on live interaction data.
Stays up to date with latest LLM advancements in prompt design, prompt optimization, few-shot learning, Tool integration protocols like MCP and AI orchestration frameworks like Agent SDK