Director, AI Experience Design Lead
Pfizer · Pennsylvania, United States · 1 mo ago
$177k–$294k/yrFull-time
About the role
This role is accountable for ensuring Pfizer's AI experiences feel coherent, trustworthy, intuitive and distinctly Pfizer across every platform and every modality. The Director, AI Experience Design Lead owns and shapes the AI experience for Pfizer colleagues globally — including how Pfizer's AI looks, sounds, and behaves — and builds and leads the team and design foundation that ships it. This role is designed for a highly experienced design leader who has evolved beyond conventional product design practices and operates at the intersection of design, AI, and engineering.
Key responsibilities
- Own, extend, and evolve Pfizer's AI-first design system for the colleague experience across human and agent surfaces: the single source of truth for how Pfizer's AI looks, sounds, and behaves
- Deliver design standards as code: tokens, patterns, and components shipped into the engineering build pipeline, so the correct, compliant pattern is the default, with accessibility (WCAG 2.1 AA) built in
- Track adoption in code (pattern usage, override rate, exception requests) and retire patterns the data shows are not working
- Connect design outcomes to measurable KPIs: adoption, task success, trust, time-to-resolution, and first-pass compliance
- Set the design bar: continuously explore emerging AI capabilities, build functional prototypes in code, introduce emerging tools and methods, validate and scale new ways AI can improve the colleague experience
- Independently own end-to-end design execution for high-impact, ambiguous initiatives, from problem framing through high-fidelity, interactive, and executive-ready prototypes
- Act as the design authority for Agentic AI experiences, including systems that plan, reason, invoke tools, and execute multi-step workflows with humans in the loop
- Own Conversational UX end-to-end (chat and/or voice), including dialog flows, conversation state, error recovery, escalation, and safe fallback behaviors
- Define assistant behaviors such as tone and voice, refusal patterns, transparency cues, and explainability, designing edge cases and failure modes in regulated contexts
- Partner closely with AI, Data, Product, and Engineering teams to co-own LLM-enabled products that balance autonomy, usability, safety, and trust
- Maintain an exceptional design bar across interaction design, visual design, systems thinking, product thinking, and storytelling
- Serve as a trusted design advisor to Product, Engineering, and Executive stakeholders across the Chief Technologist Organization's platform teams and translate complex design and AI concepts into decisions leaders can act on
- Support product vision and roadmap prioritization, helping Product and Engineering partners evaluate which AI capabilities to build, sequence, or sunset based on user value and experience impact
- Build, lead, and grow a high-performing team of AI-native experience designers: set the hiring bar, define roles, levels and growth paths, and the full talent lifecycle, establish the team's AI-native ways of working, and mentor direct reports by modeling the craft in their own work
- Own the team's operating budget and staffing across platforms and initiatives; partner with Finance on annual planning
Role behaviours
- Don't Lose Your Curiosity: Leads the practice's exploration of new design tools and methods; experiments in the open and brings validated techniques into the team's standard ways of working
- Set an Example for Your Team: Models the craft daily; ships production design work that sets the bar for the team and shows, rather than tells, how AI-first design gets done
- Act with Agency: Makes decisions without waiting for a laid-out plan; gathers just enough context and starts making, improvises around missing inputs, and corrects course with evidence from the work itself
- Care for the Craft: Holds a strong, defensible point of view on visual and interaction style; treats typography, motion, tone, and interaction detail as the product rather than the polish
- Own the Outcome: Takes accountability for experience quality and adoption on every surface the design system touches; treats pattern reuse and first-pass compliance as the team's scoreboard
- Be Polymath Oriented: Works fluently across design, engineering, and AI; translates between design intent and technical implementation and builds the team's depth beyond a single specialty
- Communicate with Precision: Sets the standard for spec-driven design communication; presents design rationale clearly to audiences from engineers to senior leadership
- Think in Systems: Designs patterns once so they scale across every platform and agent surface; connects design decisions to how the whole experience, organization, and platform behave together
Basic qualifications
- 10–15+ years of progressive experience in Experience Design, UX, or Product Design, with a proven track record of delivering complex, high-impact digital products and experiences in enterprise or highly matrixed environments
- 5+ years of direct people management experience, including hiring, developing, and leading high-performing design teams
- Working fluency with front-end development principles, APIs, and design-token pipelines, sufficient to partner with Engineering on delivering design standards as code
- Experience owning and evolving design systems and AI-first interaction patterns at scale to ensure scalability, consistency, and quality
- Deep expertise in AI-driven experience design, including hands-on experience designing Agentic AI workflows and Conversational UX (chat and/or voice), such as dialog flows, conversation state management, repair and fallback patterns, escalation models, and human-in-the-loop controls
- Advanced understanding of how AI systems behave, communicate, and build trust, including experience designing transparency cues, explainability patterns, refusal behaviors, safety guardrails, and responsible AI interaction models
- Exceptional design judgment and craft excellence, with the ability to independently produce end-to-end design work from problem framing through high-fidelity, interactive, and executive-ready prototypes
- Outstanding executive communication and storytelling skills, including the ability to clearly articulate, justify, and defend design decisions to senior leadership and diverse stakeholder groups
- Expertise in accessibility and inclusive design, with hands-on experience ensuring WCAG 2.1 AA compliance across digital products and platforms
- Strong analytical and problem-solving skills, with the ability to synthesize qualitative and quantitative inputs into clear design direction and actionable insights
- A robust portfolio demonstrating system-level thinking, AI-powered experiences, and rapid prototyping approaches, including design standards or components shipped as production code
Preferred qualifications
- Strong product design experience (not only UI): partnering with Product/Engineering to shape scope, prioritize tradeoffs, and define measurable outcomes
- Hands-on building with LLM APIs or agent frameworks to prototype real agent behavior in code, not only static interfaces
- Advanced prompt engineering skills, using prompts as detailed creative briefs that set parameters, constraints, and brand identity
- Expertise in working within lean or agile environments with fast-paced, iterative product cycles
- Track record of building design teams from the ground up, including hiring, onboarding, and career-pathing frameworks
- Experience with AI experience evaluation approaches: conversation quality testing, scenario-based risk testing, and iterative improvement loops tied to product metrics
Expert-level skills
- Craft Mastery: A recognized authority in interaction, visual, and conversation design; independently produces work from ambiguous brief to production-ready execution
- Design-Engineering Fluency: Operates where design and engineering converge; ships tokens, patterns, and standards as code and engages engineers on implementation tradeoffs
- Agentic AI Expertise: Deep working knowledge of how LLMs and agentic systems behave; designs trustworthy, transparent, and explainable experiences and anticipates failure modes
- Multi-Audience Communication: Communicates design rationale from engineering standups to executive forums and translates complex AI and design concepts into decisions leaders can act on
- Problem Discovery: Turns ambiguous, high-stakes briefs into clear design problems; the go-to person for the least defined design challenges on Pfizer's AI platforms
Physical and mental requirements
- Strong digital literacy and an "AI-first" mental model, with the ability to critically evaluate and integrate generative tools into the creative process to solve complex design challenges at scale
- Ability to manage multiple complex programs and projects simultaneously
- Strong analytical and problem-solving skills
Occasional travel may be required for workshops, team meetings, or stakeholder engagements.