Principal Engineer, Software – AI Platforms & Network Data

T-Mobile T-Mobile · Telecom · Bellevue, WA +1

Principal Engineer to lead architecture, design, and implementation of enterprise-scale AI, software, and data platforms for Network Data & AI initiatives. Focus on building reusable AI services including Generative AI, RAG, and Agentic AI, and evolving cloud-native, distributed systems for data transformation and AI-powered solutions.

What you'd actually do

  1. Lead the architecture, design, and implementation of enterprise-scale AI, software, and data platforms supporting Network Data & AI initiatives.
  2. Design and develop cloud-native, distributed systems that transform large-scale network and enterprise data into trusted data products and AI-powered solutions.
  3. Build reusable AI services utilizing Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, enterprise knowledge systems, and related technologies.
  4. Develop scalable software solutions using modern programming languages, cloud services, and distributed computing technologies.
  5. Evaluate emerging technologies and establish architectural patterns that improve scalability, reliability, security, and engineering productivity.

Skills

Required

  • Java
  • Python
  • RAG architectures
  • Agentic AI design and development
  • AI/LLM evaluation frameworks
  • Azure AI Search
  • LangChain
  • LangGraph

Nice to have

  • Demonstrated experience designing and delivering enterprise-scale software systems.
  • Strong software engineering background with experience building scalable, distributed applications.
  • Experience architecting cloud-native applications and distributed platforms.
  • Experience applying modern AI technologies, including Generative AI and Large Language Models, within production software solutions.
  • Strong analytical, problem-solving, and technical communication skills.
  • Demonstrated ability to influence technical direction across engineering teams.
  • Experience mentoring engineers and providing technical leadership.
  • Experience working with large-scale data platforms, AI-powered applications, analytics platforms, or network data environments.

What the JD emphasized

  • enterprise-scale AI
  • Generative AI
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI
  • cloud-native, distributed systems
  • scalable software solutions

Other signals

  • enterprise-scale AI platforms
  • Generative AI
  • RAG
  • Agentic AI
  • intelligent automation