Senior Engineer, Enterprise AI

T-Mobile

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Bellevue, WAFrisco, TX
Salary
$133,100–$240,100 / yr
Posted
56 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $201k
This role $187k
$120k most similar roles pay here $260k

This role pays less than 52% of similar roles. Most pay $154,900–$246,150 — the shaded band above. At the midpoint, this role pays about $187k versus about $201k for comparable roles.

Based on 240 similar postings.

Employer

About T-Mobile

T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications

T-Mobile currently has 21 open roles on FindRole.

Listed pay typically runs $127,800–$214,360 across 21 roles with salary data.

Most-posted roles

View all roles at T-Mobile

At a glance

TL;DR · Senior Engineer, Enterprise AI

Sr Engineer, Enterprise AI joins the team to design, build, and scale AI-powered applications and platforms that improve productivity and decision-making across the enterprise environment. This role involves developing enterprise-grade solutions using Large Language Models, Retrieval-Augmented Generation pipelines, and agentic AI frameworks integrated with internal systems. The engineer manages the full software development lifecycle, including architecture, prototyping, deployment, and operational support. Key responsibilities include building semantic search capabilities and integrating services with platforms like Salesforce, ServiceNow, Snowflake, Databricks, GitLab, and Atlassian. Technical requirements include experience with LangGraph, LangChain, CrewAI, AutoGen, or Semantic Kernel, alongside proficiency in CI/CD, containerization, and observability. The role addresses the challenge of creating secure, reliable, and scalable AI-driven workflows while navigating a fast-moving ecosystem to improve operational efficiency through advanced automation and intelligent systems.

What does a Engineer earn in Washington?

Median $174600 from 40 postings across 12 companies.

See salary data

What you'll do

  • Design, develop, and deploy enterprise AI applications and autonomous agents to improve operational efficiency.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines and semantic search capabilities.
  • Develop scalable integrations between AI services and platforms like Salesforce, ServiceNow, Snowflake, and Databricks.
  • Apply software engineering principles including CI/CD, observability, testing, and troubleshooting in production environments.
  • Utilize modern AI development tools and coding assistants to prototype and iterate on AI workflows.
  • Ensure enterprise AI deployments comply with governance, security, and reliability standards.
  • Evaluate emerging AI technologies and frameworks to improve platform capabilities and team technical maturity.

What we're looking for

  • Must have a Bachelor's degree in Computer Science, AI, or a related field, or an equivalent combination of education and experience.
  • Must be at least 18 years old and legally authorized to work in the United States.
  • Requires 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 is required.
  • Must have experience developing AI-enabled applications, intelligent automation workflows, or LLM-powered solutions using modern frameworks.
  • Requires experience designing or integrating distributed systems, APIs, enterprise platforms, or cloud-native applications.
  • Preferred experience includes building RAG pipelines, semantic search solutions, and agentic AI frameworks like LangChain or CrewAI.
  • Preferred experience includes integrating AI with enterprise platforms such as Salesforce, ServiceNow, Snowflake, Databricks, GitLab, or Atlassian.

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