Top Artificial Intelligence Jobs in San Antonio, TX

The Account Manager will oversee client relationships, identify growth opportunities, forecast revenue, and collaborate with internal teams to enhance client satisfaction.

The GTM Engineer II will manage strategic customer relationships, drive adoption and revenue growth, and advise executives on GTM strategy while navigating complex organizations.

The Full-Stack Software Engineer will enhance user interfaces, APIs, and develop features for AI applications while collaborating with teams and ensuring code quality.

Own and resolve complex medical billing and insurance cases end-to-end after AI handoff. Contact providers, insurers, and collections; investigate claims and benefits; advocate for users; maintain clear documentation; communicate progress; and improve playbooks while partnering with Product and Engineering.

The Enterprise Account Executive manages strategic accounts, develops client relationships, drives sales performance, and achieves quarterly quotas while utilizing the Qualtrics platform.

The Account Executive will manage strategic enterprise accounts, develop sales strategies, build relationships with senior executives, negotiate deals, and collaborate with various teams to drive revenue growth.

The Expert Mendix Developer will design and develop Mendix applications, integrate systems, ensure performance and security compliance, and mentor junior staff while collaborating with various teams.

The Principal Sales Compensation Support will design and manage sales compensation plans, oversee quotas, validate calculations, and provide insights to optimize strategies while ensuring compliance and accuracy.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.