AI Engineer (Multiple Roles)

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! AI is moving faster than almost anything else in tech right now — and someone must make sure T-Mobile moves with it, safely. That's this team. We're the engineering group deciding how new AI capability reaches the enterprise: which platforms and models get turned on, which agents are safe to keep running, and which ones need a fix before something goes wrong. Every new model, every new feature, and every agent built by every team at T-Mobile eventually runs through us. If you want to work on the infrastructure and guardrails behind AI at a company with 100M+ customers — not a side project, not a pilot, the real thing — this is that role. We're hiring across four AI Engineer positions; each pointed at a different piece of the puzzle: ● Platform Configuration & Safe Rollout — you configure our GenAI platforms (Claude, OpenAI, Glean, and whatever's next), stand up the pilot groups, and run the controlled rollout that takes a feature from test group to enterprise-wide — with security built in from the start, not bolted on after. ● Agent Risk & Remediation (2 openings) — you build the systems that scan every agent in the company, flag the ones drifting out of policy, burning too many tokens, or running on deprecating models, and push fixes across the whole fleet at scale. One of the broadest-reaching engineering roles in the org — literally every agent in T-Mobile eventually crosses your radar. ● AI Evaluation & Model Risk — you decide which models T-Mobile can trust. You own the evaluation harness, the model cards, and the ongoing checks that let teams adopt new models fast, backed by evidence instead of guesswork. Different focus, same mission: make it possible for T-Mobile to move fast on AI without ever having to choose between speed and safety. Responsibilities : Design and implement retrieval-augmented generation (RAG) pipelines to ground AI responses in enterprise knowledge sources. Develop AI models to enhance customer service automation capabilities with measurable improvements Apply prompt engineering and fine-tuning techniques to optimize AI system performance effectively Create AI tools that support integration of AI-driven improvements into operational frameworks Collaborate with cross-functional teams to ensure effective integration and functionality of AI systems Design AI systems that improve interaction capabilities within complex service workflows Contribute to strategic AI initiatives that advance organizational goals of customer satisfaction and efficiency Also responsible for other duties/projects as assigned by business management as needed Knowledge, Skills and Abilities : Required: Data Management/Data Modeling - Retrieval Augmented Generation (RAG); Vector Databases/Embeddings Prompt Engineering - LLM orchestration and RAG workflow design Python - LLM Orchestration Frameworks, e.g., LangChain, ADK Cloud Computing - RAG deployment, LLM application infrastructure, vector database/cloud AI services Data Analysis Model Tuning Customer-Focused Collaboration Education and Work Experience : Required: Bachelor's Degree plus 3 years of related work experience OR advanced degree plus 1 year of related work experience. Acceptable areas of study include Computer Science, Engineering, Artificial Intelligence, Data Science. 2+ years developing and deploying machine learning models, including fine-tuning and prompt engineering. 2+ years experience with AI tools and software development using programming languages such as Python or R. 2+ years