Strategic AI & UX Leadership
- Lead the design vision and strategy for complex AI-powered products and platforms across multiple client engagements to drive innovation and business growth
- Define and evolve design standards, frameworks, and best practices for AI-driven user experiences to ensure consistency and excellence
- Conduct strategic design research to identify emerging user needs and market opportunities in the AI space, informing product direction
- Provide thought leadership on AI-UX integration and its application across industry sectors to influence future design trends
- Influence product roadmaps and business strategy through data-driven design insights and recommendations
Advanced AI & Machine Learning Integration
- Architect sophisticated AI-driven features and functionalities that deliver measurable business value and exceptional user experiences
- Collaborate with data scientists, ML engineers, and technical architects to design scalable AI solutions aligned with user needs
- Evaluate and optimize AI model performance from a UX perspective, balancing technical capabilities with user expectations
- Design transparent, explainable AI interfaces that build user trust and understanding
Data Strategy, Analytics & Insights Leadership
- Lead the definition and execution of data strategies underpinning AI-powered products and services across client engagements
- Partner with data scientists, data engineers, and analytics teams to align data pipelines, models, and insights with user and business needs
- Translate complex datasets, model outputs, and analytics into clear, actionable insights that inform design decisions and product strategy
- Define data-driven success metrics, KPIs, and experimentation frameworks to measure AI effectiveness, user trust, and business impact
- Guide teams in leveraging quantitative and qualitative data to validate assumptions, prioritize features, and optimize user experiences
- Evaluate data quality, bias, and representativeness to ensure responsible and trustworthy use of data in AI-driven experiences
- Champion human-in-the-loop and data transparency practices, designing workflows that enable users to understand, challenge, and act on AI insights
Expert User Experience Design
- Lead end-to-end design processes for enterprise-scale projects, from discovery through delivery, ensuring high-quality outcomes
- Conduct and oversee comprehensive user research programs to gather actionable user insights
- Create sophisticated design artifacts including service blueprints, experience maps, design systems, and interactive prototypes
- Design complex, multi-platform experiences integrating AI capabilities across web, mobile, and emerging interfaces
- Oversee the design of data-rich user interfaces such as dashboards, analytics tools, and decision support systems for enterprise users
Cross-Functional Leadership & Collaboration
- Lead design thinking workshops, innovation sprints, and co-creation sessions with diverse stakeholders including C-suite executives
- Collaborate with product managers and business leaders to define product vision, strategy, and success metrics
- Bridge technical and business stakeholders by translating complex requirements into elegant design solutions
Responsible AI & Ethical Design
- Champion ethical AI practices and responsible design principles throughout all projects
- Identify and mitigate fairness, bias, privacy, and transparency issues in AI-driven experiences proactively
- Ensure compliance with regulatory requirements and industry standards in all design work
- Advocate for user rights, data privacy, and inclusive design across the organization
- Establish governance frameworks for ethical AI design practices
Google AI & Cloud AI Leadership
- Lead the design and delivery of AI solutions leveraging Google Cloud AI platforms, including Vertex AI, AutoML, and managed machine learning services
- Drive adoption of Google Generative AI capabilities (e.g., large language models, embeddings, conversational AI) to create scalable, enterprise-ready user experiences
- Partner with data scientists, ML engineers, and cloud architects to architect end-to-end AI workflows on Google Cloud, from data ingestion to model deployment and monitoring
- Define use cases and solution patterns balancing custom models and Google-managed AI services considering scalability, cost, performance, and risk
- Guide teams on MLOps best practices on Google Cloud, including model training, versioning, deployment, monitoring, and lifecycle management
- Ensure AI solutions on Google Cloud adhere to responsible AI, privacy, and security principles including explainability, fairness, and transparency
- Collaborate with client stakeholders to align Google AI capabilities with business strategy, regulatory requirements, and digital transformation roadmaps
- Evaluate and experiment with emerging Google AI services and features, translating platform advancements into practical enterprise use cases
- Provide technical and strategic leadership in designing AI-powered products integrating Google Cloud data services (e.g., BigQuery, analytics platforms)
- Support pre-sales and client engagements by shaping Google AI solution architectures, proposals, and value cases
Required competencies and certifications
- Bachelor’s or Master’s degree in Design, Human-Computer Interaction, Computer Science, AI/ML, or related field
- Minimum 3-5 years focused on AI/ML-powered products with at least 3 years of professional UX consulting experience
- Proven track record of leading complex, enterprise-scale design projects from concept to launch
- Deep understanding of AI/ML concepts, capabilities, limitations, and ethical considerations
- Expert proficiency in industry-standard design tools such as Figma, Sketch, Adobe Creative Suite, and prototyping tools
- Extensive experience with qualitative and quantitative user research methodologies
- Strong background designing for multiple platforms including web, mobile, conversational interfaces, and dashboards
- Demonstrated ability to influence product strategy and drive design-led innovation
- Exceptional communication, presentation, and stakeholder management skills, including experience influencing senior executives and C-level stakeholders
- Familiarity with Agile and Design Thinking methodologies
- Understanding of business metrics, KPIs, and how design drives business outcomes
- Familiarity with data governance, privacy, and regulatory requirements (e.g., PDPA, GDPR-aligned practices) in AI and analytics contexts
- Hands-on experience defining and tracking data-driven KPIs, success metrics, and experimentation frameworks for AI initiatives
- Strong understanding of data analytics, statistics, and applied machine learning concepts relevant to AI-powered products and services
- Experience designing or delivering AI solutions using Google Cloud AI services such as Vertex AI, AutoML, and managed ML platforms
- Familiarity with Google’s Generative AI capabilities (e.g., foundation models, LLMs, embeddings, conversational AI) and their application in enterprise products and services
- Hands-on experience integrating AI solutions with Google Cloud data services (e.g., BigQuery, data pipelines, analytics platforms) to support end-to-end AI workflows
- Strong understanding of MLOps concepts on Google Cloud including model training, deployment, monitoring, and lifecycle management
- Strong understanding of Google AI APIs for vision, natural language, speech, recommendation, or search use cases