Senior Product Designer - Okta for AI Agents

Okta•Washington, DC

15h•$136,000 - $187,000•Hybrid

About The Position

This role is for a Senior Product Designer on the Okta for AI Agents team, a critical strategic initiative focused on providing identity management, access control, and governance for AI agents and non-human identities. The team serves IT and security admins, AI developers, and system architects who need to safely deploy and govern AI agent interactions with corporate data, tools, and production environments. The designer will own key workflows end-to-end, from concepting novel interaction models for agentic permissioning to scaling flows for millions of customers. This involves partnering closely with product managers, engineers, researchers, and content designers, as well as Principal and Staff designers, to translate complex technical problems into simple and safe user experiences. The role also involves experimenting with AI in the design process itself.

Requirements

Degree in a related field or relevant work experience as a Product Designer or UX Designer.
Proficient in Figma or similar design tools.
At least a basic understanding of HTML, CSS, and JavaScript.
A digital portfolio showing depth across a variety of projects, including work that shipped and was used in real products. (Portfolio link required when applying.)
5+ years of experience as a Product Designer.
Easily move between big-picture thinking and being detail-oriented.
Curious and have experience incorporating AI into your design process, including the ability to create shared skills and workflows, iterate on ideas collaboratively with AI, and document sophisticated prompts for scaled use.
Evaluate AI-generated outputs for technical accuracy, design system adherence, and ease of use to serve as a necessary quality bar before designs move to production.
Keep user goals at the heart of your solution and can also balance business objectives and engineering considerations.
Thrive in ambiguous environments and are comfortable defining patterns, user flows and system paradigms where none exist.
Build and share empathy with people in order to deeply understand them and their needs.
See design as a partner with PM and Engineering in shaping strategic and operational product and UX outcomes.
Comfortable owning all stages of design and collaborating across teams.
Experience working with design systems, both in adhering to the system and contributing to an evolving design system.
Passionate about upholding design UX principles.
Showcase storytelling skills to communicate your design ideas to a variety of stakeholders.
Portfolio will show that you've worked on complex and challenging technical and have deep interest and ability to dive into complex technical subject matter + ability to translate complexity into user-understandable concepts.
Share our values, and work in accordance with those values.

Responsibilities

Own key workflows end-to-end, from early-stage concepting of novel interaction models, where few established patterns exist yet, through hardening and polishing flows as the product matures and scales to millions of customers.
Bring a systems-thinking lens to connect user insights with business goals, creating experiences that keep customers and their users and AI agents safe every day in this rapidly evolving space.
Design experiences across multiple personas i.e Security Admins, AI Engineers, Enterprise End-users, and IT Admins, tackling complex scenarios like AI agent lifecycle management, permission scoping, human-in-the-loop authorization, and policy enforcement across the Okta portfolio.
Contribute to scalable, usable design patterns for non-human identity and agent management and security that hold up under scale, meet a high bar for quality, and improve consistency across the product.
Regularly present work, concepts, and new ideas to cross-functional partners and senior leadership, driving alignment and gathering input to sharpen your designs.
Actively experiment with AI in your design process, using AI tools for brainstorming, rapid prototyping, exploring edge cases, and iterating on solutions, while developing judgment on where AI genuinely accelerates the work versus where it doesn’t, and sharing those learnings with the team.