Associate AI Engineer

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? Our team is searching for a Associate AI Engineer to support 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 support the design and optimization of 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 help build AI that dynamically orchestrates workflows, invokes APIs, and adapts decisions based on context and intent. You’ll support 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 in support of the advancement of 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!

: • Apply prompt engineering techniques to enhance AI model performance for customer service automation • Collaborate with cross-functional teams to integrate AI-driven enhancements into production systems • Support the development and optimization of AI models to meet operational goals • Contribute to the architecture of AI systems to improve customer interactions • Ensure the reliability, accuracy, and efficiency of AI applications in customer service operations • Fine-tune AI models to enhance performance and user satisfaction • Also responsible for other duties/projects as assigned by business management as needed Knowledge, Skills and Abilities: Required: • Data Analysis: Ability to analyze and interpret complex data to improve AI model performance. • Problem Solving: Strong problem-solving skills to troubleshoot and optimize AI systems. • Collaboration: Excellent collaboration skills to work effectively with cross-functional teams. • Data Management: Ability to work with structured and unstructured datasets while ensuring data accuracy, integrity, security, and compliance with organizational standards. • Data Modeling: Understanding of data modeling concepts and techniques, including relational, dimensional, and semantic data models used to support analytics, machine learning, and AI applications. • Model Tuning: Ability to analyze model performance, identify improvement opportunities, and implement adjustments to enhance accuracy, reliability, and scalability. • Prompt Engineering: Knowledge of prompt engineering best practices for generative AI and large language models (LLMs), including prompt design, testing, refinement, and optimization. • Cloud Computing: Knowledge of cloud computing platforms and services (e.g., AWS, Azure, Google Cloud) used for data processing, machine learning, and AI solution deployment. Preferred: • Less than 2 years Developing and optimizing AI models, particularly in customer service automation. • Less than 2 years Applying AI techniques such as prompt engineering and fine-tuning. • Less than 2 years Collaborating with cross-functional teams to integrate AI-driven solutions into production systems.