Sr Engineer, Enterprise AI

T-Mobile•Frisco, WA

6d•$133,100 - $240,100

About The Position

The Senior Engineer, Enterprise AI helps design, build, and scale AI-powered applications and platforms that improve productivity and intelligent decision-making across T-Mobile’s enterprise environment. This role focuses on developing enterprise-grade AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks integrated with internal systems and workflows. The engineer will work across the full software development lifecycle — from architecture and prototyping through deployment and operational support — while partnering closely with product, engineering, and platform teams. This role requires strong software engineering fundamentals combined with hands-on experience building and integrating AI-enabled applications in production environments. The ideal candidate is highly curious, adaptable, and comfortable working in a fast-moving AI ecosystem where technologies and approaches evolve rapidly.

Requirements

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.
Bachelor’s degree plus 3 years of related work experience OR advanced degree with 1 year of related work experience OR combination of education and experience deemed equivalent (Required)
Acceptable areas of study include Computer Science, Artificial Intelligence, or Related Field
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

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 (Preferred)
4-7 years Experience in developing and optimizing AI models for customer service automation using advanced techniques such as prompt engineering and fine-tuning. (Preferred)
4-7 years Experience in architecting and deploying sophisticated agentic AI systems to enhance reasoning and interaction capabilities in complex workflows. (Preferred)
4-7 years Experience in collaborating with cross-functional teams to integrate AI-driven enhancements into production systems. (Preferred)

Responsibilities

Design, develop, deploy, and support enterprise AI applications, autonomous agents, and intelligent workflow solutions that improve employee productivity and operational efficiency.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines, semantic search capabilities, and AI orchestration workflows integrated with enterprise platforms and data sources.
Develop scalable integrations and AI-enabled services connecting systems such as Salesforce, ServiceNow, Snowflake, Databricks, GitLab, Atlassian, and other enterprise platforms.
Partner with engineering, product, architecture, and business stakeholders to deliver secure, reliable, and scalable AI-driven solutions in production environments.
Apply strong software engineering principles across system design, coding, CI/CD, observability, testing, troubleshooting, and operational support.
Utilize modern AI development tools and coding assistants to rapidly prototype, iterate, and improve AI-enabled applications and workflows.
Contribute to AI governance, security, reliability, and compliance standards for enterprise AI deployments.
Evaluate emerging AI technologies, frameworks, and methodologies to continuously improve platform capabilities and engineering effectiveness.
Participate in architectural discussions, technical reviews, and engineering best practices to help raise the overall technical maturity of the team.
Support a highly iterative development environment where rapid experimentation, continuous learning, and fast adaptation are critical to success.