Senior Product Manager, Platform Data and Security

Since its inception in 2003, driven by visionary college students transforming online rent payment, Entrata has evolved into a global leader serving property owners, managers, and residents. Honored with prestigious awards like the Utah Business Fast 50, Silicon Slopes Hall of Fame - Software Company - 2022, Women Tech Council Shatter List, our comprehensive software suite spans rent payments, insurance, leasing, maintenance, marketing, and communication tools, reshaping property management worldwide.
Our 2200+ global team members embody intelligence and adaptability, engaging actively from top executives to part-time employees. With offices across Utah, Texas, India, Israel, and the Netherlands, Entrata blends startup innovation with established stability, evident in our transparent communication values and executive town halls. Our product isn't just desirable; it's industry essential. At Entrata, we passionately refine living experiences, uphold collective excellence, embrace boldness and resilience, and prioritize different perspectives, endeavoring to craft a better world to live in.
Entrata is seeking a Product Manager to own and scale our core platform services that safeguard user data and enable enterprise-grade access control. You’ll drive product strategy and execution across identity and access management (IAM), internal security tooling, and data governance—including authentication, SSO, permissions, audit logging, and compliance (e.g., GDPR, CCPA, DSAR). You will also lead the development of a unified data layer that powers analytics, privacy, and observability at scale.

Responsibilites

• Own the end-to-end product lifecycle for Entrata’s IAM platform, including roles/permissions and SSO.
• Lead development of security and compliance features, including audit logs, admin controls, and internal tooling.
• Define and build a unified data layer to support analytics, reporting, privacy requests, and platform observability.
• Translate regulatory and legal requirements into scalable, maintainable product features.
• Partner with engineering, infosec, legal, and platform teams to ensure alignment and secure data practices.
• Prioritize features that drive transparency, enterprise readiness, and customer trust.
• Collaborate across engineering, design, and go-to-market teams to ensure smooth execution and delivery.
• Manage roadmap planning, requirements gathering, and backlog prioritization across distributed teams.
• Integrate AI capabilities into platform features to enhance automation and user experience.
• Use data to drive product decisions, monitor performance, and continuously improve outcomes.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Business, Law, or a related field.
• 5+ years of product management experience, with at least 2 years in platform, security, or infrastructure roles.
• Strong understanding of modern software development and agile methodologies.
• Proven experience launching and managing enterprise-scale software products.
• Excellent communication skills, especially when working with technical and non-technical stakeholders.
• Experience navigating enterprise buying cycles and customer requirements.
• Comfortable managing cross-functional teams across geographies (e.g., US and India).

Preferred Qualifications

• MBA or advanced technical degree (e.g., MS in Computer Science).
• Deep familiarity with authentication protocols (OAuth, SAML), RBAC, and data protection frameworks.
• Experience working closely with legal, infosec, and engineering teams on compliance and platform integrity.
• Ability to balance regulatory nuance with technical depth.

AI Proficiency Expectations

• Prompt Engineering: Skilled in designing structured, multi-step prompts with conditional logic and context chaining.
• Context Management: Proficient at optimizing LLM input/output using structured/unstructured prompts to ensure high-fidelity results.
• LLM Knowledge: Understanding of transformer architecture, tokenization, fine-tuning, RAG, and model limitations.
• Automation Mindset: Demonstrated success deploying AI to reduce manual effort and increase speed and precision.
• Tooling Integration: Familiar with chaining LLMs with APIs, vector DBs, and code environments for dynamic workflows.
• AI Quality Control: Capable of identifying hallucinations, drift, or bias and iteratively refining systems.
• 10x Execution: Uses AI tools across ideation, delivery, and optimization to dramatically increase impact.

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Benefits: Flexible and transparent culture with remote and hybrid work options, generous vacatio