Sr Engineer, Enterprise AI

T-Mobile T-Mobile · Telecom · Bellevue, WA +2

Senior Engineer, Enterprise AI at T-Mobile, focusing on designing, building, and scaling AI-powered applications and platforms using LLMs, RAG, and agentic AI frameworks. The role involves the full software development lifecycle, integrating with enterprise systems, and ensuring secure, reliable, and scalable AI solutions in production.

What you'd actually do

  1. Design, develop, deploy, and support enterprise AI applications, autonomous agents, and intelligent workflow solutions that improve employee productivity and operational efficiency.
  2. Build and optimize Retrieval-Augmented Generation (RAG) pipelines, semantic search capabilities, and AI orchestration workflows integrated with enterprise platforms and data sources.
  3. Develop scalable integrations and AI-enabled services connecting systems such as Salesforce, ServiceNow, Snowflake, Databricks, GitLab, Atlassian, and other enterprise platforms.
  4. Partner with engineering, product, architecture, and business stakeholders to deliver secure, reliable, and scalable AI-driven solutions in production environments.
  5. Apply strong software engineering principles across system design, coding, CI/CD, observability, testing, troubleshooting, and operational support.

Skills

Required

  • 4–7 years of experience in software engineering, AI/ML engineering, platform engineering, or enterprise application development.
  • Experience building and deploying scalable software applications or platforms in enterprise environments.
  • Experience developing AI-enabled applications, intelligent automation workflows, or LLM-powered solutions using modern AI frameworks and tools.
  • Experience designing or integrating distributed systems, APIs, enterprise platforms, or cloud-native applications.
  • Experience collaborating cross-functionally with engineering, product, architecture, and business teams to deliver production solutions.

Nice to have

  • Experience building Retrieval-Augmented Generation (RAG) pipelines, semantic search solutions, or vector database integrations.
  • Experience with agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
  • Experience integrating AI solutions with enterprise systems such as Salesforce, ServiceNow, Snowflake, Databricks, GitLab, or Atlassian platforms.
  • Experience with cloud platforms, containerization, CI/CD pipelines, observability, and production operations.
  • Experience working with enterprise AI governance, security, compliance, or Human-in-the-Loop (HITL) workflows.
  • Familiarity with AI-assisted development tools and coding agents such as Claude Code, GitHub Copilot, Codex, or similar technologies.
  • Master's/Advanced Degree Computer Science, Artificial Intelligence, or Data Science
  • 4-7 years Experience in developing and optimizing AI models for customer service automation using advanced techniques such as prompt engineering and fine-tuning.
  • 4-7 years Experience in architecting and deploying sophisticated agentic AI systems to enhance reasoning and interaction capabilities in complex workflows.
  • 4-7 years Experience in collaborating with cross-functional teams to integrate AI-driven enhancements into production systems.

What the JD emphasized

  • enterprise-grade AI solutions
  • agentic AI frameworks
  • production environments
  • enterprise environments
  • AI-enabled applications
  • enterprise platforms
  • production solutions
  • production operations
  • enterprise AI governance

Other signals

  • design, build, and scale AI-powered applications and platforms
  • developing enterprise-grade AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks
  • full software development lifecycle — from architecture and prototyping through deployment and operational support
  • hands-on experience building and integrating AI-enabled applications in production environments