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Lead mid-market and enterprise grocery accounts to drive retention, growth, and expansion. Onboard retailers, run monthly reviews, interpret data into reports and case studies, coordinate cross-functional teams, and proactively mitigate churn.

The role involves designing and building AI-native systems for revenue teams at Upside, including developing applications, partnering with teams, managing the entire stack, and improving system reliability and performance.

The Principal Product Marketing Manager drives customer engagement and retention strategies, creates sales enablement materials, and collaborates with teams to enhance customer value and minimize churn.

Lead and hands-on manage the Infrastructure team owning Upside's cloud platform: drive AWS architecture (cell-based), AI-assisted deployment tooling, security, CI/CD, observability, operational excellence, and cross-functional coordination to enable reliable, scalable, and secure platform services.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

Lead consumer growth end-to-end for a hypergrowth app: own conversion, retention, cross-sell, organic growth, and multi-category adoption. Set data-driven strategy, improve product quality and trust, build habit-forming experiences, balance unit economics, and grow a team of PMs while partnering with Design, Data, and Marketing.

Own application security across the product lifecycle: run automated testing (SAST/SCA), remediate vulnerabilities, threat model, advise on secure architecture, integrate AI tools, support pen tests and bug bounty, and help administer AWS Control Tower and IAM workflows while training developers.

The Work Design Architect at Upside leads the design of the R&D Operating Blueprint to enhance organizational decision-making and processes, focusing on AI integration to improve systemic efficiency.

Own and modernize Upsides analytics data platform: migrate pipelines, reduce cost, improve governance, design reusable modeling/orchestration patterns, deliver domain-critical data products, lead cross-functional initiatives, mentor engineers, and support ML and product teams.

Lead strategy and roadmap to build a personalized growth engine using AI and marketing technology. Define requirements across data infrastructure, multi-channel outreach, app surfaces, creative personalization, and incentive systems. Run experimentation, set KPIs, drive cross-vertical adoption, and align engineering, design, data, and marketing to scale repeatable user habits and retention.