AI Engineer

T-Mobile•Bellevue, WA

2d•Onsite

About The Position

Join IntentCX, the team building the AI capabilities that are reshaping customer experience at T-Mobile. As an AI Engineer, you will help develop, refine, and scale the intelligent systems behind customer service automation, using prompt engineering, fine-tuning, AI tooling, and model optimization to improve how AI performs in complex service workflows. This role gives you the opportunity to strengthen T-Mobile’s internal ownership of critical AI solutions and intellectual property while working with cross-functional teams to bring AI-driven improvements into real production environments. If you want to build practical AI systems that improve customer interactions, increase operational efficiency, and expand the future of AI across customer experience operations, this is the role to explore. We pride ourselves on encouraging a culture of innovation, advocating for agile methodologies, and promoting transparency in all that we do. Join us in embodying the spirit of the 'Un-carrier' and make a tangible impact! Our team is dynamic where no day is the same, and we are diverse and inclusive passionate about growth and transformation. If you're up to the challenge, apply today!

Requirements

4+ yrs - Developing and deploying machine learning models, including fine-tuning and prompt engineering
4+ yrs experience with AI tools and software development using programming languages such as Python or R
2+ yrs collaborating with cross-functional teams to integrate AI solutions into business workflows
Data Analysis Ability to analyze and interpret complex data to improve AI models. (Required)
Problem Solving Capability to identify and resolve issues within AI systems and model development. (Required)
Collaboration Ability to work effectively with cross-functional teams to integrate AI solutions. (Required)
Customer Focus Focus on enhancing customer service through AI-driven solutions. (Required)
Analytics Strong analytical skills to evaluate the performance of AI models. (Required)
AI Application Development Ability to support prompt engineering, model tuning, AI tool development, and integration of AI capabilities into customer service workflows. (Required)
Evaluation and Monitoring Ability to use test results, logs, metrics, and feedback signals to assess AI system performance and support continuous improvement. (Required)
Bachelor's Degree Computer Science, Engineering, or Related Field (Required)
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience building or supporting LLM applications, conversational AI systems, agentic workflows, or AI automation.
Experience with RAG, prepared knowledge layers, tool/function calling, structured outputs, or multi-turn conversational workflows.
Experience with APIs, SQL, JSON, Git-based workflows, CI/CD, Docker, cloud deployment fundamentals, or comparable engineering tools.
Familiarity with AI observability tools such as Grafana, Splunk, Datadog, LangSmith, OpenTelemetry, Weights and Biases, or comparable platforms.
Familiarity with responsible AI practices, privacy, prompt injection risks, PII controls, model quality evaluation, or AI safety testing.
Master's/Advanced Degree Artificial Intelligence, Data Science, or Related Field (Preferred)
Certified Analytics Professional (CAP): Certification that validates an individual's expertise in data analytics processes, including the ability to model and interpret complex data. (Preferred)
Machine Learning Certification: Certification demonstrating proficiency in machine learning techniques and applications, relevant for developing AI models. (Preferred)
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. (Preferred)

Responsibilities

Develops and refines AI models to enhance customer service automation capabilities.
Applies prompt engineering and fine-tuning techniques to optimize AI system performance.
Creates AI tools to support the integration of AI-driven improvements into operational frameworks.
Supports prompt, agent workflow, context assembly, and tool integration improvements for customer-facing conversational and self-service experiences.
Builds and maintains evaluation assets such as test sets, regression checks, and validation criteria to measure AI system quality.
Uses logs, traces, dashboards, and performance metrics to diagnose AI behavior, identify defects, and support production improvements.
Collaborates with various teams to ensure effective integration and functionality of AI systems.
Designs sophisticated AI systems to improve interaction capabilities within complex service workflows.
Contributes to strategic AI initiatives to advance organizational goals of enhanced customer satisfaction and operational efficiency.