Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead the development of AI solutions and data engineering strategies. Implement AI data pipelines, collaborate with teams, and ensure the reliability of data systems.

The Performance Analytics Consultant delivers data-driven insights for GS, partnering with Underwriting and others to support performance analysis and strategic execution. Responsibilities include analyzing KPIs, developing dashboards, and ensuring data quality while communicating insights effectively to leadership.

This role involves leading the development and integration of AI solutions within the Microsoft 365 ecosystem, focusing on architecture, performance optimization, governance, and team mentorship while driving innovation in productivity.

Responsible for implementing AI data pipelines, developing AI-driven systems, and ensuring the reliability and scalability of data solutions while mentoring junior team members and collaborating with cross-functional teams.

The role involves leading AI-driven data engineering initiatives, developing data solutions, pipelines, and mentoring junior engineers while ensuring scalable and reliable systems.

Lead the design, implementation, and optimization of cloud-based contact center solutions using Amazon Connect, mentoring team members and ensuring system performance.

The VP of AI Platform leads development and governance of an enterprise AI platform, overseeing predictive modeling, generative AI, cloud operations, and team enablement, ensuring performance and compliance.

As an AI Scientist, you will design and implement generative AI solutions, support AI strategy alignment, and collaborate with teams to improve workflows in insurance.

The Software Engineering Manager leads engineering teams, guides technical strategy, manages software development processes, and mentors engineers, ensuring system stability and performance.

Design, build, and operate enterprise AI/MLOps platform services on GCP. Implement GenAI/ML solutions, architect end-to-end components, enhance platform capabilities, collaborate across teams, drive engineering execution, mentor engineers, and promote best practices for scalable, monitored AI products.