AT&T
Telecom · Telecom
- HQ
- Dallas, US
- Founded
- 2005
- Size
- 200,000+
- Website
- att.com
Currently tracking 11 active AI roles, down 67% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $87k–$1128k (avg $245k).
AT&T currently has 19 active AI-related job listings. The majority of these roles, 58%, are focused on agents. The top hiring country is the United States with 14 listings. Frequent technology tags include llm_observability, agent_orchestration, and rag. Over the last 30 days, AT&T has posted 30 new AI roles, representing a 329% increase compared to the previous 30-day period.
AT&T currently has 13 active AI-related roles in our index. The most common open titles are: Lead Software Engineering (2), AI Research Scientist (Government), Assoc Director-Cybersecurity - AI Security Engineering, Director-Technology, Lead Applications Development. Most positions are in Engineering and Research.
AT&T's active AI hiring is concentrated in: agents (62%), application (15%), serving infrastructure (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
AT&T is hiring AI talent in: United States (11 roles), India (1 role).
Job postings at AT&T most frequently reference: agent orchestration, llm observability, model serving, rag, vector db.
In the past 30 days, AT&T has posted 22 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Director-Technology Director-Technology role at AT&T focused on leading teams to develop and deliver AI-driven software solutions, including agents and agentic workflows, for wireless and wireline networks. Requires experience in enterprise software platforms, modern software engineering, and AI/ML. | Agent | 7 |
| Principal AI-Native Software Engineer Principal AI-Native Software Engineer at AT&T, blending fullstack Python engineering with hands-on experience building intelligent systems powered by LLMs, agent orchestration, and AI-augmented development workflows. The role involves partnering with business stakeholders, designing and orchestrating intelligent workflows using LLMs and multi-agent systems, developing prompts and retrieval pipelines, and using AI coding assistants. It requires strong Python development, API integration, LLM expertise, and experience with agent orchestration frameworks. | Agent |
| 7 |
| Sr Specialist Quality/M&P/Process - AI Training Manager This role focuses on managing the quality and continuous improvement of AI-powered agents that autonomously process tickets within workflow systems. Responsibilities include monitoring agent performance, reviewing and correcting fallout tickets, improving training data and knowledge bases, and ensuring compliance with business needs and regulatory standards. The role involves analyzing fallout patterns, developing training protocols, and reporting on key performance metrics. | AgentData | 7 |