Lead Data​/AI Engineering - Applied AI

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

Architect, develop, deploy, and optimize secure, scalable AI intelligence and machine learning capabilities that transform trusted enterprise data into predictive insights and decision support. Apply modern platform engineering, data engineering, statistical modeling, AI evaluation, and software development practices to move analytical capabilities from experimentation into reliable production solutions.

• AI Intelligence and Predictive Engineering: Design and product ionize forecasting, anomaly detection, driver analysis, segmentation, recommendation, and other machine learning capabilities. Translate complex business questions into measurable analytical problems, technical requirements, models, and scalable decision solutions.
• Generative AI and Evaluation: Develop AI and large language model solutions using patterns such as retrieval augmented generation, semantic search, structured outputs, tool integration, and agent workflows. Establish evaluation standards for accuracy, relevance, groundedness, explainability, consistency, performance, cost, and business value.
• Data and Semantic Engineering: Build reusable data pipelines, analytical data models, features, semantic models, and governed data products using Python, SQL, Snowflake, Databricks, or comparable technologies. Implement data contracts, lineage, validation, reconciliation, quality controls, and consistent business definitions across source systems, models, and consuming applications.
• AI Platform and Production Operations: Build the services and platform capabilities required to deploy, integrate, monitor, and scale machine learning and AI solutions. Apply version control, automated testing, continuous integration and delivery, model monitoring, data drift detection, observability, security, and lifecycle management across models, prompts, features, and evaluation datasets.
• Business Value and Technical Leadership: Partner with business, data, application, cloud, security, and architecture teams to move AI capabilities from concept through supported production use. Communicate assumptions, uncertainty, limitations, risks, and business implications while establishing reusable engineering standards and mentoring analysts and engineers.
• Technologies: Demonstrate advanced experience with Python and SQL, modern data platforms such as Snowflake or Databricks, statistical and machine learning methods, API development, and cloud platforms such as Azure. Experience with Azure Machine Learning, Microsoft Foundry, Azure OpenAI, MLflow, Docker, FastAPI, model operations, generative AI, vector search, and data observability is preferred.

An experienced professional, recognized as an expert, who creatively resolves complex AI, data, analytical, and platform challenges using broad and in depth technical knowledge. Leads significant initiatives with strategic autonomy, influences technical and executive decisions, mentors less experienced staff, and connects emerging technologies to measurable business outcomes.

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Managing very complex work related to data engineering, AI engineering, machine learning, and production platform capabilities. Solving major business problems through trusted, scalable, and measurable intelligence solutions.

Bachelor’s degree desired in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related technical or quantitative field. Equivalent professional experience will also be considered. Five or more years of related experience. Certification is required in some areas.

Our Lead Data/AI Engineering jobs earn between $ - $ 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.

• Medical/Dental/Vision coverage
• 401(k) plan
• Tuition reimbursement program
• Paid…