Lead UX Design Operations Program Manager

Target•Minneapolis, MN

1d•$115,000 - $206,000•Hybrid

About The Position

The Lead UX Design Operations Program Manager will be at the forefront of Target's evolving digital experience, shaping it for guests and contributing to business growth. The UX Operations practice focuses on the orchestration and optimization of people, processes, and practices necessary to scale high-quality user experiences across the Target enterprise. This role will leverage design program management expertise to support and develop best practices for the UX team regarding collaboration, work completion, and impact creation. The position involves partnering closely with UX and leadership to drive strategic planning, operational excellence, and execution across high-priority initiatives. Responsibilities include establishing scalable operating models, governance, and delivery practices to enable informed decision-making, navigate complexity, and successfully execute business priorities. The role acts as a trusted thought partner to senior leaders, providing visibility into portfolio health, proactively identifying risks and dependencies, and influencing decisions that shape the UX organization's direction. Additionally, the role will help advance modern ways of working by identifying opportunities to leverage AI and automation to improve planning, documentation, operational efficiency, and decision-making. In partnership with design, product, and engineering teams, the role will support the thoughtful adoption of emerging tools while maintaining quality, consistency, and governance.

Requirements

7+ years of experience in digital software product work, with inhouse or agency product design teams
Demonstrated experience organizing and delivering complex, consumer-facing digital products across the full product development lifecycle.
Experience establishing portfolio-management, program-management, and delivery practices across large, matrixed organizations.
Strong analytical capabilities, including experience defining metrics, interpreting product and operational data, identifying patterns, and translating insights into decisions and action.
Proven ability to build trusted partnerships with senior leaders, influencing strategic decisions across a highly matrixed organization.
Strong AI fluency and practical experience applying generative AI, AI agents, automation, or machine-learning-enabled tools within UX or digital product-development workflows.
Technical acumen and the ability to collaborate with designers, engineers, product managers, data practitioners, design-system teams, platform teams, and technology leaders.
A systems-thinking mindset, with the ability to understand the interconnected relationships among customer needs, team workflows, product platforms, technology constraints, organizational structures, and business priorities.

Responsibilities

Partner with UX and cross-functional senior leaders to define portfolio strategy, operational priorities, roadmaps, and execution plans for high-impact consumer-facing digital product initiatives.
Lead cross-functional programs spanning UX, Product, Engineering, Data, and business teams, driving alignment, managing dependencies, mitigating risks, and ensuring delivery against customer and business objectives.
Establish governance practices that improve planning, prioritization, execution visibility, accountability, and operational consistency across the UX organization.
Help teams introduce AI-assisted and agentic workflows into the product development lifecycle, including workflows supporting research, synthesis, concept development, prototyping, content creation, design systems, design-to-code, engineering handoff, testing, documentation, and delivery management.
Partner with UX, Product, Engineering, and Technology leaders to assess where AI agents, coding companions, automation, and connected platforms can improve product-development speed, quality, consistency, and decision-making.
Lead pilots and structured experimentation for emerging AI tools and workflows, defining hypotheses, success measures, human-in-the-loop controls, evaluation criteria, and plans for responsible adoption and scale.