Lead Tech Business Mgmt - AI Software Engineer

AT&T; United States; On-site; USD 120,000 - 165,000; Full time

Job summary

AT&T is seeking an AI Software Engineer to design, build, and maintain data-driven solutions that connect systems, automate processes, and generate actionable insights.

The role blends software engineering, data engineering, analytics, and AI/ML, focusing on rapidly learning new technologies, integrating disparate systems, and delivering scalable solutions with strong data governance.

Qualifications

• Experience building APIs and data pipelines.
• Strong SQL skills and working with enterprise-scale datasets.
• Experience with cloud platforms and data ecosystems.

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 for data exchange.
• Ensure data quality, governance, security, and lineage standards are met.
• Design scalable data pipelines and data models for reporting and AI initiatives.
• Partner with business teams to identify AI-driven process improvements.
• Design and develop dashboards, reports, and visualizations for business decisions.

Skills

Python

Java

C#

Tools

Power BI

Tableau

Looker

Job description

NOTE: AT&T will not hire any applicants for this position who require employer sponsorship now or in the future. (Including, STEM-F1/OPT, H1b, H4, or TN)

Lead Tech Business Mgmt - AI Software Engineer

We are seeking a highly adaptable and technically versatile AI Software 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.

Key Responsibilities

Systems Integration & API Development

• 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.

Technology Evaluation & Continuous Learning

• 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.

Required Qualifications

Technical Skills

• Strong software development experience using one or more
• modern programming languages:
• Python
• Java
• C#
• 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.

Data & Analytics

• 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

AI / ML

• Familiarity with:
• Generative AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG) or other knowledge systems
• AI APIs and model integration

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.

Critical Success Factors

The ideal candidate:

• Learns new technologies exceptionally fast.
• 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.

Preferred Experience

• 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.

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.