Responsibilities
- Hands-On Design Partnership: Act as a vocal, engaged, and proactive design partner within a cross-functional team (engineers, strategists, product), delivering rapid prototypes that solve complex business problems.
- Agentic & Conversational Leadership: Lead the design of Agentic AI experiences (systems that plan, make decisions, call tools, and complete multi-step workflows with humans in the loop) and own Conversational UX end-to-end.
- Assistant Behavior Design: Design and document assistant behaviors, including tone and voice, grounded responses, refusal patterns, transparency cues, and trust-building interaction patterns.
- Design System Pattern Ownership: Own specific pattern areas of the AI-first design system (assistant UI components, conversation templates, disclosure components, escalation patterns) and ship them as code into the engineering build pipeline.
- Agent Simulation & LLM Collaboration: Create interactive prototypes that simulate agent behavior to validate workflows and risks quickly, partnering closely with Engineering, Data, and AI teams on LLM-enabled experiences.
- QA & Guardrail Management: Maintain the reference library behind automated design quality checks, including voice patterns, disclosure templates, accessibility checks, and regulated-content guardrails.
- Pattern Adoption & Standards Drift: Monitor pattern usage, override rates, and exception requests for your assigned surfaces; surface standards drift and refine system-wide standards based on real-world data.
- Playbooks & Libraries: Create reusable playbooks and pattern libraries for agentic workflows and conversational design (escalation, repair, safety responses, approvals, and multi-step task orchestration).
- Enablement & Mentorship: Proactively train and informally mentor peer designers and cross-functional partners on the rapid prototyping process, AI tools, and design system integration.
- Product-Minded Design Strategy: Act as a strategist who frames problems, defines hypotheses, influences roadmaps, and connects design decisions to measurable outcomes like task success, adoption, and trust indicators.
Requirements
- Experience: 7-10 years of progressive UX design experience with a proven track record of delivering high-impact digital products.
- AI Experience: Extensive experience working with AI-driven design tools and platforms, with a deep understanding of leveraging them for rapid prototyping and iterative design.
- Conversational UX Expertise: Demonstrated experience designing Conversational UX (chat and/or voice), including dialog flows, conversation state, repair/fallback patterns, escalation, and tone/voice guidelines.
- Agentic AI Workflows: Demonstrated experience designing Agentic AI workflows (systems taking action via tools/functions), including human-in-the-loop controls, approvals, transparency, and safe failure modes.
- Mindset: An "AI-first" mindset with a proven willingness to challenge traditional design paradigms and adopt augmented workflows to radically accelerate delivery cycles.
- Design Systems Integration: Experience shipping design system components and patterns (such as design tokens or documented components) directly into engineering pipelines.
- Accessibility Leadership: Hands-on expertise ensuring WCAG 2.1 AA compliance across a wide variety of digital platforms.
- Portfolio: A robust portfolio demonstrating experience with system-level design thinking, AI-powered experiences, and advanced rapid prototyping techniques.
- Communication & Leadership: Exceptional communication skills with a proven ability to lead without authority, manage ambiguity, and present/justify design decisions to senior leadership and diverse stakeholder groups.
Nice to Have
- Experience defining responsible AI UX patterns (transparency/disclosures, explainability cues, privacy boundaries, and trust/safety guardrails).
- Comfort using AI-assisted coding tools to prototype ideas, weigh implementation tradeoffs, and partner closely with engineering.
- Advanced product design experience partnering with Product and Engineering to prioritize tradeoffs and define measurable outcomes.
- Previous experience designing within the healthcare or pharmaceutical sectors.
- Experience with AI experience evaluation approaches (conversation quality testing, scenario-based risk testing, and iterative improvement loops tied to product metrics).
- Strong knowledge of service design, journey mapping, or customer experience frameworks.
