Senior Product Manager, Incentives

Augeo Affinity Marketing•St Paul, MN

4d•Hybrid

About The Position

Augeo's Applied AI team builds THEO, the orchestration and intelligence layer behind the reward, recognition, incentive and advocacy programs our clients run. We are hiring a Senior Product Manager to own the Incentives domain: the THEO capability set that brings intelligence and automation to performance incentive programs, enabling organizations to configure programs, evaluate participant performance, identify earned outcomes, and orchestrate rewards and payouts at scale. Today, THEO Reward capabilities power personalized reward search, discovery, and redemption in client marketplaces, with recommendations from an ML model trained on more than four million interactions. Within the next six to twelve months we expect to be in market with both THEO Incentives and THEO Recognition capabilities supporting new and existing clients, alongside continued expansion of personalized rewards and offers. The Applied AI team is organized into four capability pods. (1) Intelligence/ML has a product manager and an AI architect/data scientist. (2) Rewards, (3) Recognition, and (4) Incentives each have a product manager and an AI architect. You would lead the Incentives pod with the Incentives AI Architect and partner most closely with Intelligence/ML on the models and signals behind incentive decisions. THEO sits at Augeo's core, and its capabilities are built for every business unit rather than rebuilt inside each one. An incentive program for a Workplace client runs on the same THEO capability as an incentive program for an Advocacy client. This role works across all of Augeo’s business units to identify shared requirements and to maintain the boundary between what THEO owns and what each unit builds on top of it.

Requirements

5-8 years of product management experience, with meaningful ownership of a product area from strategy through launch and iteration.
Product fundamentals : writing clear requirements, prioritizing a roadmap against limited engineering capacity, running discovery, and defining success metrics before you build.
Experience shipping ML-driven products : you have owned features where a model does the core work, such as ranking, pricing, recommendations, or personalization.
Fluency in AI/ML technical concepts : you can work directly with data scientists and engineers on model evaluation, prompting, and system design without being an ML engineer yourself.
Analytical rigor : comfortable defining metrics, interrogating data, and making prioritization calls from evidence rather than opinion.

Nice To Haves

Experience shipping a generative AI or LLM-based feature to production, from prototype through general availability.
Experience with loyalty, rewards, incentive, or engagement platforms.
Hands-on experience with the methods behind treatment assignment, such as uplift modeling, contextual bandits, or holdout testing, and with the personalization and recommendation systems they power.
Familiarity with incentive and reward program economics: points liability, breakage, redemption modeling, or partner cost structures.
Hands-on use of AI-powered development and prototyping tools (e.g., Claude Code) to accelerate product discovery and delivery.

Responsibilities

Own the product vision, strategy, and roadmap for the Incentives domain, from problem discovery through shipped, measured outcomes.
Define how AI and ML models select, personalize, and sequence incentives (rewards, points, offers) to maximize engagement and program ROI for clients and partners.
Partner with data science and engineering to specify the incentive decisioning engine: the inputs it draws from THEO's user profiles and behavioral signals, model evaluation criteria, and production quality bars.
Translate incentive economics (budgets, redemption rates, breakage, partner cost structures) into product requirements that balance member value with program sustainability.
Design and prioritize the incentive catalog and configuration experience so clients and partners can launch and manage programs with minimal manual overhead.
Build the experimentation practice for incentives, using holdout tests and uplift modeling to measure what a reward actually caused rather than what merely correlated with it.
Evaluate where generative AI and agentic workflows can automate incentive content generation, catalog curation, or program configuration, then ship the highest-leverage ones first.
Turn client, partner, and internal stakeholder needs into precise, prioritized requirements with clear success metrics.
Ensure incentive products meet privacy, consent, and data governance requirements across enterprise client environments.
Represent the Incentives pod in cross-team planning, clearly communicating tradeoffs, risks, and progress to engineering, design, and commercial leadership.

Benefits

Medical, Dental and Vision coverage with additional perks through third party vendors offering more virtual and in person care at your fingertips (must be in select locations)
Paid Long-Term disability and Life Insurance
HSA/FSA plans
Varying voluntary benefits such as critical, hospital, pet coverage and much more
Employee benefit education, campaigns and wellness opportunities
401k retirement matching and financial planning resources
Education reimbursement
Several EAP resources
13 paid holidays and PTO time
Rewards, incentives and gamification for birthdays, Work-aversery's, professional and personal milestones, company involvement and kudos
Employee referral bonuses
Employee group opportunities
Fun, casual and flexible working environment that embraces the hybrid workstyle
Career growth opportunities