Jobs at 84.51°

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 revenue accounting and close activities for a multi-channel media and analytics business. Ensure GAAP-compliant revenue recognition, manage reconciliations and controls, support financial reporting and variance analysis, partner cross-functionally, drive process improvements and system implementations, and mentor revenue accounting team members.

Lead design and implementation of Databricks/Azure data solutions to ingest, store, transform, and distribute large-scale retail data. Own features through the SDLC, mentor engineers, lead cross-functional collaboration, build REST APIs on Kubernetes, execute testing, and set technical strategy with Product, Data Science, and Architecture.

Design, build, and maintain Databricks and cloud-based data ingestion, storage, and distribution solutions. Implement ETL/warehousing, pipeline orchestration, CI/CD, automated testing, and mentor junior engineers while collaborating across architecture and scrum teams to deliver scalable data products.

As a Senior Client Success Manager, you will manage client relationships, drive media and incentive activation strategies, and ensure successful campaign execution and optimization.

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.

Own and evolve enterprise data platform capabilities for data quality, freshness, reliability, and dependency discovery. Define 12-month roadmaps, translate business goals into product requirements, partner with engineering and data teams for delivery, monitor adoption and product health, maintain core product artifacts, and drive cross-functional adoption and enablement.

Lead design and delivery of cloud-native, AI-ready data architectures and semantic layers. Define data models, integration patterns, governance, and migration roadmaps. Guide technical decisions, build reference implementations, mentor teams, and ensure security, cost management, and observability for production-grade AI and analytics platforms.

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.

The role involves supporting investment reporting and performance analytics for Kroger and CPG partners using data insights to drive decision-making and optimize funding.

The Lead Technical Product Manager drives AI product strategies, manages development teams, and ensures alignment on product goals while prioritizing business value.