This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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. 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. 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.
Job Responsibility:
Architects agentic AI systems that accomplish sophisticated tasks by invoking AI models as well as internal and third-party tools using APIs, ensuring flawless data flow in production environments
Optimizes performance of agentic AI systems through prompt engineering, fine-tuning and reinforcement learning using T-Mobile’s customer interaction data
Develops and maintains supporting software components and scripts to enable AI model deployment, testing, evaluation and monitoring
Implement retrieval-augmented generation (RAG) techniques to ensure AI responses are contextually accurate and grounded in real-time data
Stay at the forefront of LLM advancements, incorporating the latest techniques in prompt design, few-shot learning, Tool integration protocols like MCP and AI orchestration frameworks like Agent SDK
Collaborates with backend engineers, business experts and conversation designers ensuring AI-driven enhancements are optimally integrated into production environments
Defining success metrics that aligns with business requirements and continuously evaluate and improve model quality based on those metrics
Participates in other duties or projects as assigned by business management as needed
Requirements:
Deep expertise in LLM fine-tuning and prompt engineering (e.g., OpenAI APIs, Hugging Face, Anthropic Claude, Google Gemini)
Strong experience with AI orchestration tools (e.g., LangChain, LlamaIndex, vector databases for retrieval augmentation)
Hands-on knowledge of function calling and API-based reasoning models (e.g., using structured outputs to drive automated workflows)
Proficiency in Python and AI development frameworks for building scalable AI applications
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, Artificial Intelligence, or equivalent
At least 18 years of age
Legally authorized to work in the United States
Nice to have:
Experience in customer service AI applications, particularly intent-driven automation
Familiarity with RAG pipelines and vector database retrieval for augmenting AI responses
Background in AI middleware development, such as AI-powered function calling and API integrations
Knowledge of cloud AI services (AWS/GCP/Azure) and scalable AI architectures
Masters degree in Computer Science or Artificial Intelligence preferred