AI Engineer (Multiple Roles)

T-Mobile•Bellevue, WA

2d•Onsite

About The Position

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.

Requirements

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
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 collaborating with cross-functional teams to integrate AI solutions into business workflows.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Certified Analytics Professional (CAP): Certification that validates an individual's expertise in data analytics processes, including the ability to model and interpret complex data.
Machine Learning Certification: Certification demonstrating proficiency in machine learning techniques and applications, relevant for developing AI models.
Certified Data Scientist (CDS): Certification that endorses skills in data science and its application in AI modeling, crucial for enhancing AI-driven customer service solutions.

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