Sr AI Engineer

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Engineer the intelligent core of T-Mobile’s next-generation customer experience.

We’re seeking a Senior AI Engineer to architect and optimize the agentic AI systems driving the evolution of customer service. You’ll design AI that performs with precision and coordinates across models, internal APIs, and third-party tools to create reliable, production-grade workflows and intuitive customer interactions.

Using advanced techniques such as prompt engineering, model fine-tuning, evaluation frameworks, and system-level orchestration, you’ll improve the accuracy, reliability, and reasoning capabilities of AI across the enterprise. Working closely with engineering, product, and operations teams, you’ll bring these innovations to life in resilient, fault-tolerant environments supporting millions of real-world customer conversations.

This is an opportunity to help define the AI foundation of the Un-carrier and build intelligent systems that set a new standard for customer experience. If you’re passionate about engineering quality, solving complex problems, and making a meaningful customer impact, we invite you to apply.

RESPONSIBILITIES

· Design, develop, and deploy scalable, production-grade Generative AI applications, LLM-powered solutions, and agentic AI systems to support enterprise business operations and customer service automation.

· Architect and implement sophisticated AI agents and multi-agent orchestration workflows using modern frameworks such as LangGraph, LangChain, or equivalent technologies.

· Develop Retrieval-Augmented Generation (RAG) solutions leveraging embeddings, vector databases, semantic search, and enterprise knowledge sources.

· Build and integrate RESTful APIs, Model Context Protocol (MCP) connectors, and enterprise data services to enable secure AI interactions with internal and external systems.

· Optimize AI performance through prompt engineering, model selection, retrieval optimization, fine-tuning, and efficient inference strategies to enhance customer service automation.

· Design and implement AI evaluation frameworks to measure accuracy, hallucination rates, reliability, latency, throughput, and cost efficiency, ensuring alignment with strategic objectives and customer satisfaction goals.

· Develop cloud-native AI solutions using Azure, AWS, or equivalent platforms, incorporating containerization, automated deployment, and scalable architectures.

· Implement security, governance, and responsible AI practices, including authentication, authorization, data privacy, prompt injection protection, and enterprise compliance requirements.

· Establish observability, logging, monitoring, and troubleshooting capabilities for AI applications and agentic workflows in production environments.

· Collaborate with cross-functional engineering, architecture, product, cybersecurity, and business teams to ensure seamless integration of AI-driven enhancements into production systems.

· Conduct technical design reviews, participate in code reviews, mentor engineers, and contribute to reusable engineering standards and best practices.

· Research and evaluate emerging AI technologies, open-source frameworks, and industry advancements to stay current with the latest methodologies applicable to customer service and to identify opportunities for innovation and continuous improvement.

· Perform other duties and projects as assigned by business management.

Skills

REQUIRED

· Programming: Strong proficiency in Python, software engineering principles, and object-oriented programming.

· API Development: Experience designing, developing, securing, and integrating RESTful APIs using frameworks such as FastAPI or equivalent.

· Generative AI and LLMs: Hands-on experience building applications using large language models, prompt engineering, structured outputs, function calling, and tool integration.

· Agentic AI: Experience developing AI agents, tool-calling workflows, and orchestration solutions using LangGraph, LangChain, or similar frameworks.

· RAG and Data Management: Knowledge of embeddings, vector databases, semantic retrieval, document processing, and data integration.

· Cloud Computing: Experience developing and deploying applications on Azure, AWS, or Google Cloud.

· Software Engineering and DevOps: Proficiency with Git, CI/CD pipelines, automated testing, and production software development practices.

· System Architecture: Ability to design scalable, secure, reliable, and maintainable distributed applications.

· Data Analysis and Modeling: Strong analytical skills and experience working with structured and unstructured data.

· AI Evaluation: Understanding of model evaluation, performance benchmarking, accuracy measurement, and AI quality assurance.

· Collaboration: Strong communication, problem-solving, and cross-functional collaboration skills.

PREFERRED

· Experience with Model Context Protocol (MCP) and enterprise AI tool integrations.

· Experience with Docker, Kubernetes, and cloud-native deployment tooling for AI workloads.

EDUCATION & EXPERIENCE

REQUIRED

· Bachelor's Degree plus 5 years of related work experience

OR advanced degree with 3 years of related work experience

PREFERRED

· Acceptable areas of study include Computer Science, Artificial Intelligence, or Related Field

Master's/Advanced Degree Computer Science, Artificial Intelligence, or Data Science

· 4+ yrs experience in developing and optimizing AI models for customer service automation using advanced techniques such as prompt engineering and fine-tuning.

· 4+ yrs experience in archi