Artificial Intelligence Jobs in Irving, TX

The Lead AI Engineer will manage AI/ML model production, ensure deployment pipelines, mentor teams, and enhance AI systems with innovative technologies.

The Senior Digital Product Manager will lead the AI Platform roadmap, drive development of core capabilities, and ensure performance evaluation, while collaborating across teams to deliver impactful AI solutions.

The role involves developing and prototyping Generative AI applications, implementing AI models, managing data pipelines, deploying applications using MLOps, and collaborating with teams to innovate and integrate AI technologies.

The Lead Software Engineer, ServiceNow AI is responsible for designing and developing ServiceNow solutions, integrating AI and automation functionalities, and providing technical leadership to the team.

Design, build, and support an AI-ready enterprise data enablement platform using Databricks, dbt, Delta Lake, and Azure data services. Create reusable CI/CD and IaC accelerators, govern data products via Unity Catalog, enable analytical access with Starburst/Trino, troubleshoot production issues, and collaborate with cross-functional teams to deliver governed, reusable, and production-grade data products for analytics and GenAI use cases.

Serve as enterprise strategic advisor on AI and automation by researching market and vendor trends, evaluating emerging capabilities, developing evidence-based adoption recommendations, supporting investment and roadmap planning, and briefing senior leaders. Maintain competitive intelligence, assess risks and governance implications, and collaborate with business, product, and governance stakeholders to align strategy and execution.

Design and build automated data validation and monitoring systems across clinical and AI pipelines. Translate business needs into validation frameworks, implement Python/C#/SQL checks, perform root-cause analysis, and embed data quality and compliance (HIPAA/SOC2) into data lifecycles. Collaborate with stakeholders to prioritize, deploy, and document automation and AI-assisted tooling.

Lead operationalization and validation of Agentic AI and GenAI solutions: define validation frameworks, analyze production agent data, create observability dashboards, detect anomalies/hallucinations, support deployments and A/B testing, and deliver actionable insights to improve models and business outcomes.