Lead Data/AI Engineering - Applied AI

AT&T•Dallas, TX

2d•Onsite

About The Position

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. Overall Purpose: 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.

Requirements

Advanced experience with Python and SQL
Experience with modern data platforms such as Snowflake or Databricks
Experience with statistical and machine learning methods
Experience with API development
Experience with cloud platforms such as Azure
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.

Nice To Haves

Experience with Azure Machine Learning
Experience with Microsoft Foundry
Experience with Azure OpenAI
Experience with MLflow
Experience with Docker
Experience with FastAPI
Experience with model operations
Experience with generative AI
Experience with vector search
Experience with data observability

Responsibilities

Design and productionize 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.
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.
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.
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.
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.

Benefits

Medical/Dental/Vision coverage
401(k) plan
Tuition reimbursement program
Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
Paid Parental Leave
Paid Caregiver Leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
Employee Assistance Programs (EAP)
Extensive employee wellness programs
Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone