Principal Product Manager - Customer Technologies

GEICO•Bethesda, MD

2d•Hybrid

About The Position

This Principal Product Manager role owns the customer and data foundation for GEICO’s platform for creating and activating customer communications and marketing campaigns. The platform is evolving into a modern customer engagement platform, helping teams reach the right customers with relevant experiences across channels, with growing emphasis on self-serve usability, multi-channel orchestration, AI engagement, and enterprise-grade reliability. This role defines the vision, platform patterns, and roadmap that connect audience, customer data, AI-enabled engagement inputs, and the platform foundation that powers personalized, intelligent customer engagement. The role drives automation and simplification across audience and platform workflows, strengthens customer and audience capabilities, and helps teams activate experiences with confidence. It also leads product direction for intelligent and agentic engagement capabilities, including AI-assisted audience development, goal-based engagement strategy, and the data quality and platform patterns to support agentic workflows at scale. This position is hybrid, requiring on-site presence 2-3 days a week in Palo Alto, CA; Seattle, WA; or Bethesda, MD.

Requirements

8+ years of product management experience, with at least 3 years focused on audience management, customer data platforms, martech, segmentation, or related customer engagement domains.
Proven experience delivering platform or internal product capabilities at enterprise scale, with ownership spanning multiple engineering squads or platform domains.
Strong understanding of audience and segmentation workflows, customer data, data activation, eligibility, and the operational realities of marketing and campaign teams.
Demonstrated ability to drive automation and simplification in complex products, reducing manual work and improving how teams get work done.
Experience defining platform integration patterns or shared capabilities consumed by adjacent product teams.
Ability to partner effectively with engineering, design, data engineering, and business stakeholders in complex, cross-functional environments.
Strong strategic thinking with the ability to connect product roadmaps to business goals, portfolio priorities, and customer outcomes.
Excellent communication, storytelling, and stakeholder management skills, including executive alignment.
Experience defining KPIs and using data to inform prioritization and product decisions.
Bachelor’s degree or equivalent practical experience.

Nice To Haves

Experience with customer data platforms, audience activation, or enterprise data platforms.
Familiarity with journey orchestration, campaign management, or cross-channel engagement platforms.
Experience with AI-assisted product capabilities, intelligent targeting, or goal-based engagement design.
Track record of simplifying complex internal platforms through automation, guided experiences, or intelligent defaults, with demonstrable gains in user efficiency or business performance.
Exposure to regulated industries, consent and preference management, or enterprise platform reliability expectations.
Advanced degree or relevant product, data, or martech certifications.

Responsibilities

Define and evolve the product vision, strategy, and roadmap for customer engagement and data capabilities.
Own how audience, customer data, and engagement context integrate across journey orchestration, content creation, and delivery.
Define platform patterns, contracts, and integration approaches that partner product teams and engineering squads build on.
Connect roadmap priorities to measurable engagement performance, including reach, relevance, activation success, data quality, and time to launch.
Translate complex business, data, and operational requirements into clear product strategies and actionable features.
Drive the Audience Manager product surface, including audience creation, segmentation, reference audiences, suppression, execution, and lifecycle management.
Advance the customer and audience data layer that journeys and content depend on, including modernization of how audience capabilities are used across the platform.
Define engagement context for users, including who can be reached, on which channels, and with what data quality and eligibility constraints.
Establish product patterns for governance, validation, and safeguards that reduce errors, rework, and operational risk.
Define product direction for AI-assisted and agentic capabilities across customer engagement, including intelligent audience development, goal-based engagement, and data-driven decision support for who to reach and why.
Establish the customer, audience, and data foundation for agentic workflows, including eligibility, channel readiness, data quality, and governance guardrails.
Partner with AI engineering to translate intelligent engagement opportunities into usable product experiences that fit existing marketer and operator workflows.
Identify high-value agentic and automation opportunities across audience creation, targeting, activation readiness, and engagement planning.
Ensure AI and agentic capabilities are transparent, trustworthy, and responsible for business users, with clear guardrails in a regulated, high-volume environment.
Improve data quality signals in product, including audience fit, coverage, and readiness for activation.
Advance integration and activation patterns with customer data and audience platforms so definition and activation feel connected, not fragmented.
Partner with data and platform engineering teams to ensure audience and customer data capabilities scale reliably.
Identify and remove friction across audience and related platform workflows through automation, clearer workflows, and self-serve experiences.
Contribute to platform-wide priorities around workflow simplification, platform trust, and reduced operational dependency.
Balance speed and ease of use with the safeguards and governance in a regulated, high-volume environment.
Lead discovery with audience builders, campaign managers, marketing operations, data partners, and engineering teams.
Prioritize features based on customer impact, business value, strategic alignment, and effort using qualitative insight and quantitative data.
Define KPIs that reflect platform performance and downstream engagement impact.
Lead cross-functional teams through the full product lifecycle from discovery and design to delivery and measurement.
Operate as the customer and data spine across the platform product team, partnering with peer product managers across journey, content, and delivery.
Influence and align senior stakeholders on product direction, tradeoffs, and outcomes.
Represent customer and data capabilities in stakeholder intake and portfolio planning.
Mentor product managers and contribute to product practice.