Lead Tech Business Mgmt - AI Data Engineer

We are seeking a highly adaptable and technically versatile AI Data Engineer to design, build, and maintain data-driven solutions that connect systems, automate processes, and generate actionable insights.
 

This role requires a strong blend of software engineering, data engineering, analytics, and AI/ML expertise. The ideal candidate is comfortable working with unfamiliar technologies, learning new platforms quickly, and integrating disparate systems through APIs and automation.
 

Success in this role depends less on experience with any single technology stack and more on the ability to understand complex business problems, rapidly acquire new technical knowledge, and build scalable solutions that bridge data, applications, and AI capabilities.

• 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 software solutions and rapidly develop working integrations.
   

• Extract, transform, and load (ETL/ELT) data from multiple structured and unstructured data sources.
• Design scalable data pipelines and data models to support reporting, analytics, and AI initiatives.
• Work directly with raw, complex, and potentially incomplete datasets to create trusted data assets.
• Ensure data quality, governance, security, and lineage standards are met.
• Optimize data processing workflows for performance and reliability.
   

• Integrate AI services, LLMs, predictive models, and intelligent automation capabilities into business workflows.
• Support development and deployment of AI and machine learning solutions.
• Prepare, transform, and engineer data for ML and GenAI use cases.
• Partner with business teams to identify opportunities for AI-driven process improvements.
• Evaluate emerging AI technologies and recommend practical business applications.
   

• Design and develop dashboards, reports, and visualizations that drive business decisions.
• Translate complex datasets into intuitive and actionable insights.
• Work closely with leadership and business stakeholders to define KPIs and success metrics.
• Build self-service analytics solutions where appropriate.
   

• Rapidly learn unfamiliar systems, platforms, and technologies.
• Assess new tools and determine technical feasibility, integration requirements, and business value.
• Serve as a technical problem solver capable of navigating ambiguity.
• Stay current with emerging trends in AI, machine learning, analytics, cloud technologies, and software development.

• Strong software development experience using one or more modern
  programming languages:
  • Python
  • Java
  • C#
  • JavaScript/TypeScript
• Experience building and consuming APIs and web services.
• Strong SQL skills and experience working with enterprise-scale datasets.
• Experience developing data pipelines and automation workflows.
• Understanding of cloud platforms and data ecosystems.
• Experience creating analytics solutions and data visualizations.
• Familiarity with AI/ML concepts and modern AI platforms.
   

• Experience working directly with raw data sources.
• Strong data modeling and transformation skills.
• Proficiency in dashboard and reporting platforms such as:
  • Power BI
  • Tableau
  • Looker
  • Similar BI tools

• Familiarity with:
  • Machine Learning
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG) or other knowledge systems
  • AI APIs and model integration

• Capable of integrating multiple enterprise systems through APIs or other mechanisms.
• Ability to understand and map complex business processes across platforms.
• Experience with workflow orchestration and automation solutions.

The ideal candidate:

• Learns new technologies exceptionally fast.
• Is comfortable operating in ambiguous environments.
• Can independently investigate unfamiliar systems and determine how to integrate them.
• Thinks in terms of end-to-end solutions rather than individual technologies.
• Bridges the gap between business problems and technical implementation.
• Can communicate effectively with both engineers and non-technical stakeholders.
• Demonstrates curiosity, initiative, and a strong ownership mentality.
• Is equally comfortable discussing APIs, data pipelines, AI models, and executive dashboards.

• Building AI-enabled business solutions.
• Cloud platforms (Azure, AWS, or GCP).
• Data warehouses and lakehouses.
• Snowflake, Databricks, Fabric, Synapse, or similar platforms.
• Git, CI/CD, and DevOps practices.
• Event-driven architectures and messaging platforms.
• MLOps or AI deployment frameworks.
• Enterprise workflow automation.

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.