Job Description

The Data Security team is responsible for safeguarding the organization's most critical asset-its data-by ensuring confidentiality, integrity, and availability across all platforms and environments. Working at the intersection of cybersecurity, data governance, and privacy, the Data Security team focuses on capabilities such as data classification, encryption, secure data access, and monitoring. The team partners closely with engineering, risk, and business units to embed security controls throughout the data lifecycle-from creation and storage to sharing and archival.

As a Product Owner, you will lead the development of platforms and capabilities that enable internal teams to securely leverage enterprise data encryption services. This role focuses on building and enhancing a services portal for encryption solutions, as well as products that integrate with Hardware Security Modules (HSMs). You will play a critical role in shaping the direction of encryption products-driving innovation, accelerating AI adoption, improving automation, and enhancing the efficiency and scalability of security services across the organization. You will champion the responsible use of AI across the product lifecycle, identifying opportunities to improve customer experiences, streamline engineering workflows, and enable secure AI-powered capabilities within enterprise security platforms. You should have strong product mindset with the ability to translate complex technical capabilities into scalable, user-focused solutions.

How will you make an impact in this role?

The Product Owner is accountable for translating product direction into precise, executable work while ensuring strong alignment with engineering delivery and measurable outcomes. This role emphasizes disciplined backlog management, clear prioritization, and consistent execution patterns to improve delivery predictability, reduce fragmentation, and enhance overall product quality. You will act as the voice of the customer and the steward of execution excellence-ensuring that encryption services are delivered securely, reliably, and with a high degree of operational rigor.

This role also plays a key part in enabling the evolution of the platform to support AI-driven use cases-ensuring that encryption services are accessible, intuitive, and scalable for both human users and intelligent systems. The Product Owner will incorporate AI capabilities into product development in a disciplined, execution-focused manner, aligning innovation with secure, reliable delivery.

Responsibilities

Product Ownership & Delivery
• Own and manage the product backlog across one or more teams, ensuring it is continuously refined, prioritized, and aligned with delivery outcomes and engineering capacity.
• Translate product direction into epics, features, and user stories with clear, testable acceptance criteria and minimal ambiguity.
• Ensure a consistently ready backlog that supports uninterrupted execution and predictable delivery.
• Drive standardization and consistency in how work is defined and delivered across encryption services.

Stakeholder Collaboration
• Act as the primary liaison between engineering teams, stakeholders, and leadership to ensure tight alignment on priorities and execution.
• Collaborate with stakeholders to clarify requirements, reduce ambiguity, and ensure work is scoped for efficient delivery.
• Communicate progress, risks, dependencies, and trade-offs with clarity and transparency.
• Ensure alignment between business needs, engineering constraints, and platform scalability goals.

Agile Execution
• Lead and actively participate in Agile ceremonies (planning, backlog refinement, stand-ups, reviews, retrospectives) with a strong focus on execution quality.
• Provide real-time clarification and decision-making support to engineering teams during sprints.
• Ensure completed work meets defined acceptance criteria and quality standards before acceptance.
• Identify and remove blockers to maintain delivery momentum and reduce delays.

Value Delivery & Prioritization
• Prioritize backlog items to maximize measurable outcomes, including delivery efficiency, platform scalability, and user experience improvements.
• Balance short-term delivery commitments with long-term platform health, extensibility, and consistency.
• Make informed, data-driven trade-offs across scope, timeline, and quality.
• Focus on reducing delivery fragmentation and improving throughput across teams.

Quality & Continuous Improvement
• Ensure delivered features meet functional expectations, usability standards, and operational requirements.
• Drive continuous improvement in delivery processes, backlog quality, and execution discipline.
• Incorporate feedback from users, engineers, and stakeholders to refine priorities and improve outcomes.
• Contribute to improving the usability, scalability, and extensibility of the Data Security Services Portal, including readiness for AI-driven interactions and integrations.
• Leverage AI-enabled tools and approaches to enhance prioritization, accelerate delivery, and improve product quality.
• Incorporate AI-enabled capabilities into the Data Security Services Portal to improve usability, automate workflows, and enable more intelligent, secure interactions for engineers, agents, and emerging AI-driven use cases.

- Measure and communicate the impact of AI adoption using productivity, quality, and customer outcome metrics.

- Partner with engineering teams to identify secure, scalable approaches for integrating AI into enterprise products and workflows.

- Establish best practices for the responsible use of AI within product management and software delivery.

- Evaluate emerging AI capabilities and recommend practical applications that create measurable business value.

- Champion the adoption of AI across the product organization, identifying opportunities to improve team productivity, accelerate delivery, and enhance customer experiences.

- AI Leadership & Innovation

Qualifications

Minimum Qualifications

• 5+ years Product Owner or execution-focused delivery experience.
• 7+ years of experience working with Agile/Scrum teams in a fast-paced development environment including experience driving execution discipline across multiple teams and improving delivery predictability and consistency.
• Proven experience managing backlogs and delivering software products end-to-end including ownership of complex, multi-team backlogs with measurable delivery outcomes and reduced fragmentation.
• Comfortable engaging with engineering teams on technical requirements, dependencies, and constraints including deep partnerships with engineering on execution trade-offs, scalability, and implementation consistency.
• Experience supporting multiple Scrum teams simultaneously (strongly preferred).
• Skilled in breaking down large initiatives into incremental, testable, and deliverable user stories.
• Ability to lead effective backlog refinement sessions, stakeholder discussions, and decision-making meetings.
• Proven product mindset-ability to connect business value, user needs, and technical execution.
• Excellent communication, prioritization, and stakeholder management skills.
• Strong analytical thinking and ability to make data-driven decisions.
• Demonstrated experience using Generative AI tools (e.g., ChatGPT, GitHub Copilot, Microsoft Copilot, Claude, Gemini, or similar) to improve product management, documentation, analysis, or software delivery workflows.
  • Strong understanding of AI, Generative AI, Agentic AI, and Large Language Model (LLM) concepts, including opportunities, limitations, governance considerations, and secure enterprise adoption.
• Bachelor Science in Computer Science or Information Technology or equivalent technical experience.

Preferred Qualifications:

• Certified Scrum Product Owner (CSPO) or equivalent certification.
• Experience working in scaled Agile environments (SAFe or similar).
• Data-driven mindset with experience using metrics to guide decisions.
• Experience leading AI adoption initiatives within product or engineering organizations, including integrating AI into product strategy, operational workflows, or software delivery practices.
• Experience defining AI-powered product capabilities, including conversational interfaces, intelligent automation, AI agents, or retrieval-augmented applications.
• Familiarity with responsible AI principles, model governance, prompt engineering, and secure AI implementation in regulated environments.
• Familiarity with encryption, tokenization, and other data security concepts.
• Experience working with enterprise security platforms or regulated environments.
• Familiarity with programming languages (Java, ReactJs etc..) and concepts