AI Engineer
Chicago, IllinoisAll locationsChicago, IllinoisSt. Petersburg, FloridaDetroit, MichiganSt. Louis, MissouriRichmond, VirginiaRaleigh, North CarolinaDallas, TexasIndianapolis, IndianaMinneapolis, MinnesotaAnnapolis, MarylandAtlanta GeorgiaBaton Rouge, LouisianaBoston, MassachusettsColumbus, Ohio Remote
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About the role
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. 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 what goes to production. This is not a research role. You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks
What you'll bring
- As a remote-first organization headquartered in St.
- Petersburg, Florida, Kobie values meaningful in-person connection and collaboration that strengthens our teams, supports our clients, and enhances our culture.
- While travel requirements vary by role, periodic travel may be required to support business objectives, team collaboration, customer engagements, training, and company events.
- Candidates should be able and willing to travel as needed to fulfill the responsibilities of the role.
- 3+ years of professional Python, with production experience building and operating services
- 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
- Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel
- Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
- Experience designing evaluation frameworks ( MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
- Fluency with Git, Docker, and modern API frameworks
- Clear written communication and the judgment to know when something is ready to ship
- Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts.