Lead AI & Data Integration Engineer

AT&T; Dallas (TX); On-site; USD 119,000 - 178,000; Full time

Benefits offered by this job

Medical/Dental/Vision coverage

401(k) plan

Tuition reimbursement program

Paid Time Off and Holidays

Paid Parental Leave

Paid Caregiver Leave

Disability Benefits

Life and Death Insurance

Employee Discounts

Job summary

AT&T in Dallas, Texas is seeking a Lead Tech Business Mgmt - AI Software Engineer to design, build, and maintain data-driven solutions that connect systems, automate processes, and deliver actionable insights.

This role blends software engineering, data engineering, analytics, and AI/ML, requiring quick learning, API integration, and the ability to translate business problems into scalable, end-to-end solutions.

Qualifications

• Experience building and consuming APIs and web services.
• Strong SQL skills and experience with enterprise-scale datasets.
• Experience developing data pipelines and automation workflows.
• Cloud platforms experience (Azure, AWS, or GCP).
• Experience creating analytics solutions and data visualizations.
• Familiarity with AI/ML concepts and modern AI platforms.

Responsibilities

• Design, develop, and maintain integrations between internal and external platforms.
• Build and consume REST and other API-based services.
• Develop middleware, connectors, and automation workflows that enable seamless data exchange across systems.
• Troubleshoot integration issues and optimize performance, reliability, and scalability.
• Evaluate new platforms and rapidly develop working integrations.

Skills

Python

Java

C#

JavaScript/TypeScript

APIs & Web Services

SQL

Cloud platforms

Data pipelines

AI/ML concepts

LLMs

Tools

REST APIs

CI/CD

Job description

AT&T in Dallas, Texas is seeking a Lead Tech Business Mgmt - AI Software Engineer to design, build, and maintain data-driven solutions that connect systems, automate processes, and deliver actionable insights.

This role blends software engineering, data engineering, analytics, and AI/ML, requiring quick learning, API integration, and the ability to translate business problems into scalable, end-to-end solutions.