Kobie Marketing

AI Engineer

RemoteRemote OKContract$140k – $220k / year

About this role

Kobie Marketing - AI Engineer AI Engineer St. Petersburg, Florida / Detroit, Michigan / St. Louis, Missouri / Richmond, Virginia / Raleigh, North Carolina / Dallas, Texas / Indianapolis, Indiana / Minneapolis, Minnesota / Annapolis, Maryland / Atlanta Georgia / Baton Rouge, Louisiana / Boston, Massachusetts / Chicago, Illinois / Columbus, Ohio Business Intelligence – Innovation / Full-Time / Remote apply for this job Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We’re always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world’s most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. Join Us from Anywhere While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: · Flexible Time Off to recharge when needed · Nine Company-Wide Holidays · A diverse suite of benefits prioritizing your growth, development, and personal well-being Discover more about our perks and benefits here. Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. About the team and what we’ll build together Kobie runs some of the largest loyalty programs in the world. We're building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams and clients an LLM-native way to work with complex loyalty logic. We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of wha

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