Job DescriptionThe
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
We are seeking a hands-on
Technical Project Manager to accelerate delivery across our Data Security engineering teams. This role is embedded within day-to-day engineering workflows and is accountable for ensuring that product backlog priorities are translated into high-quality, demonstrable outcomes that meet stakeholder needs.
This position is central to our transformation to a product-driven Data Security organization, strengthening alignment between product intent and engineering execution. A key differentiator is the active use of AI to improve backlog quality, accelerate delivery, and increase the consistency and precision of engineering outputs.
This role ensures that engineering teams are consistently working on the right priorities with well-defined requirements, and delivering high-quality outcomes that meet stakeholder expectations. By embedding AI into backlog management and sprint execution, the role increases speed, reduces rework, and improves consistency across teams, enabling more scalable and predictable delivery.
Responsibilities- Drive execution across multiple Scrum teams, ensuring product backlog priorities are clearly defined, aligned to stakeholder needs, and delivered with high quality
- Own end-to-end backlog readiness, including AI-assisted story creation, refinement, and decomposition into clear, testable, and demonstrable sprint deliverables
- Ensure strong alignment between Product Owners, stakeholders, and engineering teams so that delivered work meets intended outcomes and business value
- Use AI to enhance backlog quality, including generating acceptance criteria, identifying gaps, surfacing edge cases, and improving requirement clarity before development begins
- Embed AI into sprint workflows to accelerate decision-making, reduce ambiguity, and improve delivery consistency
- Facilitate Scrum ceremonies and actively shape sprint plans to ensure achievable, outcome-driven commitments
- Monitor and improve delivery metrics such as velocity, predictability, and quality, using data and AI insights to continuously optimize performance
- Rapidly identify and resolve blockers to maintain momentum across multiple teams
- Drive consistent standards for backlog hygiene, definition of ready, and definition of done
Qualifications- 10+ years of experience as a Technical Project Manager/ Scrum Master/ Business Analyst within a large enterprise software engineering environment
- 7+ years of experience with designing & implementing encryption strategies to protect sensitive customer data, encryption, and platform engineering environment
- 5+ years of experience with Jira, Confluence & ITSM tools.
- Demonstrated experience managing and refining product backlogs to deliver measurable, stakeholder-aligned outcomes in financial services or other regulated industries
- Strong understanding of Agile and Scrum methodologies with experience supporting multiple teams through transformations
- Proven ability to translate complex requirements into clear, actionable, and testable engineering work
- Hands-on experience using or integrating AI tools to improve delivery workflows, backlog quality, or engineering outcomes
- Strong communication and stakeholder alignment skills, with a focus on clarity and accountability
- High attention to detail and a strong bias toward quality and execution and ability to hold teams accountable for delivery in a positive manner
- Familiarity with developer platforms, APIs, or shared services models
- Experience scaling Agile delivery practices across multiple teams and overcoming adoption challenges
- Bachelor's degree in computer science/technology/engineering/Science/ business management or equivalent experience is mandatory.
Preferred: Master's Degree in management, computer science, engineering or a related discipline is strongly desired
