Lead Data/AI Engineering - Applied AI
Summary
Lead Data/AI engineer at AT&T in Dallas (on-site 5 days/week) building and productionizing ML, GenAI, and LLM solutions on Azure, Snowflake/Databricks, and Python. Owns forecasting, anomaly detection, RAG, and agent workflows plus the platform/MLOps layer (Docker, FastAPI, MLflow) to deploy and monitor models at scale.
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.
Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:
- AI Intelligence and Predictive Engineering: 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.
- 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.
Job Contribution: 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.
Supervisor: No
TCP Career Step Differentiator: 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.
Education/Experience: 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 $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.
Joining our team comes with amazing perks and 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
Weekly Hours:
40Time Type:
RegularLocation:
Dallas, TexasSalary Range:
$158,200.00 - $237,400.00AT&T and its subsidiaries are committed to equal employment opportunity. All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws. In addition, AT&T will provide reasonable accommodations to qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made. Click here to learn more or request an application accommodation here.