AI Software Development Architect

AT&T

Confirmed live today High trust
Closes in 6 days

Quick summary

Work type
On-site
Location
Dallas, TX
Salary
$189,200–$283,800 / yr
Posted
2 days ago
Freshness
Confirmed live today
Closes
Nov 5, 2026 (soon)

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k
This role $236k
$134k $300k
below market most similar roles pay here above market

This role pays more than 80% of similar roles. Most pay $162,000–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About AT&T

AT&T is a US-based telecommunications company providing wireless, broadband, and fiber internet service along with phone and connectivity products for consumers and businesses.

AT&T currently has 93 open roles on FindRole.

Listed pay typically runs $98,100–$196,000 across 83 roles with salary data.

Most-posted roles

View all roles at AT&T

At a glance

TL;DR · AI Software Development Architect

The AI Software Development Architect joins the engineering organization to serve as a technical architect, advisor, and AI engineering expert. This role focuses on transforming software engineering by helping teams adopt AI-first practices and modern coding technologies. You will design, develop, and optimize production-grade agentic AI solutions, LLM inference architectures, and AI-powered automation capabilities. Key responsibilities include building foundational AI platforms like Agent365 and AI Gateway while improving developer productivity and software quality. You will utilize the NVIDIA technology stack, Claude Code, Windsurf, and Codex to create reusable frameworks and scalable architectures. The work involves translating complex business requirements into practical, repeatable AI solutions that optimize workloads, reduce token consumption, and establish enterprise governance for large-scale software engineering lifecycle practices.

What you'll do

  • Design, develop, and optimize agentic AI solutions to support software engineering and developer productivity.
  • Apply hands-on expertise with the NVIDIA technology stack to build production-grade enterprise AI solutions.
  • Design and optimize LLM inference architectures for performance, scalability, reliability, and cost efficiency.
  • Build AI-powered automation capabilities and enhance enterprise AI governance platforms like Agent365 and AI Gateway.
  • Translate complex business requirements into scalable, production-grade AI and machine learning architectures.
  • Coach engineering teams on adopting AI-first development methodologies, tools, and best practices.
  • Create reusable frameworks, architectural patterns, and training materials to scale AI adoption across the enterprise.
  • Establish metrics to communicate the impact of AI-enabled development initiatives on productivity and business outcomes.

What we're looking for

  • PhD in an approved field with at least 4 years of relevant experience; or
  • Master’s degree in an approved field with at least 6 years of relevant experience; or
  • Bachelor’s degree in an approved field with at least 8 years of relevant experience.
  • Hands-on experience working with the NVIDIA AI technology stack.
  • Deep technical knowledge of large language model inference.
  • Experience designing and implementing production-grade AI, machine learning, or agentic AI solutions.
  • Experience with AI-assisted software development tools and modern AI engineering practices.
  • Experience optimizing AI solutions for performance, scalability, observability, and cost efficiency.
  • Experience with AI coding and agentic development tools such as Claude Code, Windsurf, or Codex (preferred).
  • Experience developing enterprise AI platforms, gateways, governance solutions, or reusable AI frameworks (preferred).
  • Experience implementing AI solutions across large-scale software engineering organizations (preferred).
  • Ability to influence technical direction and coach engineering teams without direct management responsibility (preferred).

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