Jobs at 84.51°

Supports digital and retail media campaign activation across onsite, offsite, and in-store channels. Responsibilities include campaign setup, trafficking, quality assurance, launch readiness, pacing and performance monitoring, reporting, client onboarding, billing support, and issue escalation. The role partners with sales, client partnerships, campaign operations, creative, and product teams while learning company tools, processes, and compliance requirements for regulated categories.

Leads product strategy, roadmap, governance, and delivery for the Salesforce platform supporting commercial and lead-to-revenue processes. Defines business requirements, data models, workflows, integrations, security, and acceptance criteria while balancing platform health, scalability, and business value. Partners with architecture, engineering, commercial, finance, marketing, and operations teams to drive Salesforce modernization, automation, AI adoption, seller experience improvements, and product commercialization across Media Cloud and related capabilities.

Lead the Agentic Foundations engineering team to design, build, and operate enterprise-grade agentic platforms and tooling. Provide technical and operational leadership across AI agent registries, deployment, monitoring, reliability, and developer-facing abstractions while hiring and managing engineering teams and offshore reliability resources.

Develops and governs Salesforce reports, dashboards, and commercial analytics supporting pipeline management, forecasting, revenue visibility, opportunity tracking, and executive decisions. The role investigates data discrepancies, maintains reporting governance, improves data quality, enables self-service analytics, supports Salesforce adoption, and identifies automation and AI-readiness opportunities. It partners with Sales, Finance, Product, Engineering, and leadership to translate business needs into scalable reporting solutions.

Provide technical leadership for search and recommender systems: design, prototype, and deploy production-ready ML solutions (including LLM and agent-based methods); define evaluation and experimentation frameworks; partner with engineering on real-time serving, feature pipelines, and monitoring; drive cross-functional alignment and mentor data scientists.

Lead the roadmap for an enterprise AI platform supporting reusable agent infrastructure, context capabilities, deployment patterns, evaluation, observability, governance, and feedback loops. Partner with Data Science, Engineering, and product builders to prioritize platform investments, manage delivery tradeoffs, drive adoption, measure impact, and establish reliable AI development standards across Kroger Precision Marketing.

Lead Applied AI product initiatives: identify and co-develop high-impact AI use cases, lead prototypes/MVPs with cross-functional teams, drive adoption of GenAI and AI Enablement capabilities, champion responsible and explainable AI, run AI ideation workshops, manage AI Spoke network, track business value, and own product responsibilities (OKRs, roadmaps, planning, Jira execution).

Lead a forward-deployed engineering function that enables enterprise adoption of AI coding tools. Embed with delivery teams, write software, document learnings, monitor adoption through observability tools, identify platform and policy gaps, maintain internal plugin marketplaces, manage SLAs and incidents, and participate in on-call and business-hours support. Collaborate with platform, security, infrastructure, product, and development teams to scale AI-enabled software delivery.

Lead applied AI initiatives by co-developing AI agents, embeddings-based solutions, and proprietary language-model applications with business teams. Identify AI use cases, develop rapid proofs of concept, mentor junior team members, create trainings and technical documentation, guide production implementations, troubleshoot integrations, and collaborate with engineering partners to deliver modular solutions.

Designs and delivers architectures for AI-enabled products across data platforms, APIs, cloud applications, machine learning workflows, and event-driven integrations. Partners with product, engineering, data science, security, and business teams to translate needs into technical designs, prototypes, implementation plans, and scalable production solutions. The role also defines API and governance patterns, evaluates emerging AI technologies, supports delivery teams, and mentors engineers on architecture and pragmatic technical execution.

Lead strategy and execution for an AI Platform domain: set vision, manage multiple product teams, define measurable outcomes, build operating systems and reusable capabilities, partner with engineering and commercial teams, drive adoption, and coach product leaders to deliver production-ready, responsible AI features that create business impact.

Lead development of AI workforce platform infrastructure, including deployment automation, CI/CD pipelines, observability, configuration standards, prompt and skill marketplaces, MCP integrations, and workflow playbooks. Partner with engineering teams to embed AI tooling into development workflows, improve platform capabilities, document best practices, and provide technical leadership. The role includes production-quality coding, cross-functional communication, on-call participation, and business-hours customer support.

Leads the creation of an enterprise AI Reliability Engineering discipline, establishing production standards, SLOs, observability, AgentOps, incident response, resilience, quality controls, cost optimization, and safe deployment practices. Builds and leads a multidisciplinary engineering team while partnering across platform, AI, infrastructure, security, and Responsible AI organizations to ensure reliable, high-quality, scalable operation of models, agents, gateways, and shared AI services.