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84.51°
Cincinnati, OH
Source: 84.51° careers · View original posting
From 84.51°'s posting. “We” and “our” refer to the employer.
84.51° Overview:
84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.
Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.
84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.
Join us at 84.51°!
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PLEASE NOTE: This role is on the Kroger Technology & Digital (KTD) team. KTD is the technology division of The Kroger Co. responsible for building, operating, and innovating the digital infrastructure and software that powers Kroger’s retail stores, e-commerce platforms, supply chain, and corporate operations. There is a strong collaboration between KTD and 84.51°.
Role Summary
The Senior Manager, AI Reliability Engineering at KTD leads the engineering discipline that makes enterprise AI operationally trustworthy at scale. As the enterprise moves from AI pilots to production systems that associates and customers depend on every day, this leader ensures that models, agents, copilots, AI gateways and shared runtime services are dependable, high-quality, responsive and cost-efficient by design. This leader will stand up a new discipline from the ground up: defining what production-grade AI means, engineering
the standards and automation that bake reliability and quality into every system, and shaping how build teams design for resilience from day one. The role blends engineering leadership, technical ownership and cross-functional influence. Reliability is a strategic enabler of adoption and velocity - the difference between experimenting with AI and confidently running it at scale.
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