Lead Consultant

Job description

What you will do

Strategic AI & UX Leadership

– Lead the design vision and strategy for complex AI-powered products and platforms across multiple client engagements

– Define and evolve design standards, frameworks, and best practices for AI-driven user experiences

– Conduct strategic design research to identify emerging user needs and market opportunities in the AI space

– Provide thought leadership on the future of AI-UX integration and its application across industry sectors

– 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

– Partner closely with data scientists, ML engineers, and technical architects to design scalable AI solutions

– 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 that underpin 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, product strategy, and roadmaps

– 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, ensuring responsible and trustworthy use of data in AI-driven experiences

– Champion human-in-the-loop and data transparency practices, designing workflows where users can 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

– Conduct and oversee comprehensive user research programs

– Create sophisticated design artifacts including service blueprints, experience maps, design systems, and interactive prototypes

– Design complex, multi-platform experiences that seamlessly integrate AI capabilities across web, mobile, and emerging interfaces

– Oversee the design of data-rich user interfaces, including 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 various stakeholders, including C-suite

– Collaborate with product managers and business leaders to define product vision, strategy, and success metrics

– Bridge technical and business stakeholders, translating complex requirements into elegant design solutions

Responsible AI & Ethical Design

– Champion ethical AI practices and responsible design principles

– Proactively identify and mitigate fairness, bias, privacy, and transparency issues in AI-driven experiences

– Ensure compliance with regulatory requirements and industry standards across all design work

– Advocate for user rights, data privacy, and inclusive design throughout 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 the 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 that balance 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 built on Google Cloud follow 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 that integrate 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

Qualifications

– Bachelor’s or Master’s degree in Design, Human-Computer Interaction, Computer Science, AI/ML, or related field

– At least 3-5 years focused on AI/ML-powered products, with 3 years of professional UX consultant experience.

– Proven track record of leading complex, enterprise-scale design projects from concept to launch

– Comprehensive portfolio demonstrating strategic thinking, design process excellence, and measurable business impact

– Deep understanding of AI/ML concepts, capabilities, limitations, and ethical considerations

– Expert proficiency in industry-standard design tools (Figma, Sketch, Adobe Creative Suite, prototyping tools)

– Extensive experience with user research methodologies, both qualitative and quantitative

– Strong background in designing for multiple platforms (web, mobile, conversational interfaces, dashboards)

– Demonstrated ability to influence product strategy and drive design-led innovation

– Exceptional communication, presentation, and stakeholder management skills

– Experience presenting to and 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.