> Markdown version of [/jobs/ext/4600727-lead-data-ai-engineering](https://www.wearedevelopers.com/jobs/ext/4600727-lead-data-ai-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data/AI Engineering - **Company:** AT&T Inc. - **Location:** Dallas, TX, United States - **Experience:** Expert - **Salary:** $158,200.0 - $237,400.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Continuous Integration, Information Engineering, Data Integrity, Python (Programming Language), Rapid Prototyping Process, Scala (Programming Language), Scientific Computating, Software Engineering, Statistical Process Control (SPC), SQL Databases, Transmission Control Protocol (TCP), Google Cloud, Snowflake, Apache Spark, Information Technology, Performance Monitor, Apache Kafka, Graphql, Api Design, Software Version Control, Databricks, Programming Languages, Microservices - **Published:** November 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6ecfa23994cef524 ## About the Role Education/Experience: Bachelor's degree (BS/BA) desired such as Computer Science or Scientific Computing. 5+ years of related experience. Certification is required in some areas. Our Lead Data/AI Engineering jobs earn between $158,200.00 - $237,400.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training. ## Description Typical tasks may include, but are not limited to, the following: * Design, Development, Testing, and Deployment: Lead the creation of scalable Data & AI applications using best practices in software engineering such as automation, version control, and CI/CD. Develop and implement rigorous testing strategies to ensure application reliability and performance. Oversee deployment processes, addressing issues related to configuration, environment, or security. * Engineering and Analytics: Translate Data & AI use case requirements into effective data models and pipelines, ensuring data integrity through statistical quality procedures and advanced AI techniques. * API & Microservice Development: Architect and build secure, scalable microservices and APIs, ensuring broad usability, security, and adherence to best practices in documentation and version control. * Platform Scalability & Optimization: Evaluate and select optimal technologies for cloud and on-premise deployments, implementing strategies for scalability, performance monitoring, and cost optimization. * Technologies: Demonstrate expertise with Data & AI technologies (e.g., Spark, Kafka, Databricks, Snowflake), programming languages (e.g., Java, Scala, Python, SQL), API development patterns (e.g., HTTP/REST, GraphQL), and cloud platforms (e.g., Azure, AWS, GCP). * As part of the Revenue Operations Reinvention Lab, this role will design, build and deploy targeted data and agentic AI solutions that improve Revenue Operations productivity. The engineer will focus on Smaller, high-value use cases that fall outside quarterly enterprise technology roadmaps, while ensuring solutions are secure, maintainable, measurable, and aligned with broader technology architecture. * Identify and prioritize high-value opportunities: Partner with Rev Ops stakeholders to discover workflow bottlenecks, repetitive tasks, and decision-support needs that can be addressed through focused data, automation, or agentic AI solutions. * Own the end-to-end delivery of targeted Rev Ops data and agentic AI solutions - from use-case discovery and rapid prototyping through controlled deployment, measurement, documentation, and operational handoff - while aligning with enterprise platforms, architecture, and governance requirements. Job Contribution: An experienced professional, recognized as an expert, creatively resolving complex issues with broad and in-depth knowledge. Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less experienced staff, implements long-term plans impacting the organization, and frequently collaborates with senior leadership. Supervisor: No TCP Career Step Differentiator: Managing very complex work related to data engineering and AI. Solving major business problems.