Jobs at 84.51°

Provides strategic consultation, training, and hands-on support to clients using 84.51° insights platforms. Drives platform adoption, connects retail and shopper data to business needs, supports merchandising and media strategies, tracks value creation, advises on research design, and communicates client feedback to product teams. The role requires client-facing consulting or sales experience, retail and consumer insights knowledge, data-driven storytelling, stakeholder management, and proficiency with 84.51° platforms.

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.

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.

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.

Serve as a strategic partner to CPG clients, managing integrated media and incentive activations from planning through optimization and reporting. Develop data-driven activation strategies, lead client communications, monitor campaign performance, resolve issues, and identify cross-sell and up-sell opportunities. Collaborate with sales, account management, media, insights, and campaign operations teams to deliver accurate, timely campaign execution and commercial growth.

Serve as a strategic client partner for CPG brands, driving media and incentive-based activation across planning, execution, optimization, and reporting. Lead client communications, campaign pacing, troubleshooting, and performance storytelling while identifying cross-sell and up-sell opportunities. Collaborate with sales, account, media, insights, and operations teams to ensure flawless activation and KPI achievement.

Lead a portfolio of clients and a small team to drive retention, organic growth, and client outcomes across Media, Incentives, and Insights. Build senior client and Kroger relationships, own renewal and growth strategies, run business planning and reviews, partner cross-functionally to remove execution barriers, and develop team capabilities while improving operational consistency and client value.

Lead end-to-end client partnerships for 84.51° products, build digital media plans, prospect and grow CPG and agency relationships, drive revenue against quota, coordinate cross-functional execution, use insights and CRM to inform strategies, and support advertising campaign delivery. Requires frequent client engagement and travel.

Own product strategy and execution for AI-powered SDLC tooling. Define roadmaps, translate developer workflows into requirements, deliver scalable AI developer tools, measure adoption and value, manage cross-functional agile teams, and ensure governance, security, and responsible AI practices.

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 product owner for the AI Gateway platform driving roadmap, prioritization, backlog management, cross-functional delivery, stakeholder management, and measurement of AI product value. Requires translating business needs into technical requirements, defining acceptance criteria, and partnering with engineering, UX, and data science to deliver AI/Generative AI 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.