Purpose of Position
The Head of AI Innovation will be responsible for driving the exploration, development, and adoption of AI capabilities across the organization, with strong focus on large language models, data science, machine learning, and applied algorithms to solve real business problems. The incumbent will identify high-value AI opportunities, lead technical experimentation, and translate innovation into scalable enterprise solutions that enhance productivity, customer experience, and decision-making.
The incumbent will collaborate closely with business stakeholders, product, engineering, data, security, and external partners to shape the AI roadmap, establish practical use cases, and build a strong foundation for responsible, scalable, and business-aligned AI innovation in a fast-paced and dynamic environment.
Job Description
Lead the AI innovation strategy, roadmap, and execution across the organization, identifying high-impact opportunities where AI, machine learning, and advanced analytics can create measurable business value.
Drive the research, evaluation, prototyping, and scaling of AI solutions with strong focus on LLMs, data science, and algorithmic approaches for both internal productivity and customer-facing use cases.
Partner with business leaders and cross-functional teams to define problem statements, assess feasibility, prioritize use cases, and convert opportunities into executable AI initiatives.
Provide strong technical leadership in model selection, prompt engineering, retrieval-augmented generation, fine-tuning approaches, evaluation methodology, and AI solution architecture.
Lead the design and implementation of AI and data science solutions including forecasting, recommendation, personalization, search relevance, classification, anomaly detection, and optimization use cases.
Work closely with data, engineering, and platform teams to ensure AI solutions are production-ready, secure, scalable, maintainable, and integrated into enterprise systems and workflows.
Establish standards and best practices for experimentation, model evaluation, benchmarking, monitoring, governance, and continuous improvement across AI initiatives.
Ensure responsible AI adoption by partnering with security and technology leadership on data privacy, access control, model risk awareness, and policy alignment.
Evaluate and manage external vendors, technology partners, and emerging tools where relevant to accelerate innovation and delivery outcomes,
Build, mentor, and lead a high-performing AI innovation team, fostering a culture of experimentation, technical excellence, business understanding, and continuous learning.
Communicate AI strategy, use case value, and technical direction clearly to both technical and non-technical stakeholders, including senior leadership.
Elevate CASETiFY’s AI capabilities and employer branding to attract top talents in AI, data science, and advanced engineering.
Requirements
Strong hands-on experience in LLMs, machine learning, data science, and algorithm development, with practical experience in building business-focused AI solutions.
Solid technical expertise in generative AI, prompt engineering, retrieval-augmented generation, fine-tuning approaches, and model evaluation for enterprise use cases.
Strong foundation in statistics, machine learning methods, predictive analytics, and data-driven problem solving.
Strong algorithmic thinking with experience in designing analytical, optimization, or decision-support solutions for real business scenarios.
Experience in developing end-to-end AI or data science solutions from ideation, experimentation, and validation through to deployment and business adoption.
Strong understanding of data pipelines, model lifecycle, experimentation frameworks, MLOps practices, and integration with enterprise applications and workflows.
Hands-on coding proficiency in Python and familiarity with common AI, machine learning, and data science frameworks and tools.
Ability to balance innovation with practicality, and translate technical possibilities into scalable business value.
Excellent stakeholder management with strong business acumen and the ability to work across multiple business units and technology functions.
Experience in leading or mentoring technical teams including AI engineers, data scientists, machine learning engineers, or related talent.
Strong communication and presentation skills, with the ability to explain complex AI concepts to technical and non-technical audiences.
Known for promoting best practices, technical rigor, and responsible innovation.
At least 8 years of relevant working experience in AI, data science, machine learning, advanced analytics, or related technology roles, with leadership experience preferred.
Previous experience in eCommerce, retail, customer experience, digital products, or operational analytics is highly preferred.
Experience with cloud AI platforms, modern data ecosystems, and model deployment frameworks is preferred.
Proficient in spoken and written Chinese and English.