VP of Data & AI Strategy leading innovative AI - driven payment product designs. Championing AI design thinking and facilitating collaboration across Mastercard's diverse product teams.
About the role
- Lead the design and delivery of end-to-end AI/ML pipelines, ensuring solutions are scalable, resilient, and aligned with business objectives
- Develop and deploy advanced ML, DL, and LLM models
- Integrate AI capabilities into enterprise platforms and products in a governed, model-agnostic, and future-proof manner
- Implement monitoring and observability to manage drift, bias, fairness, and performance
- Establish guardrails for responsible AI adoption, covering explainability, bias detection, security, and compliance
- Mentor and guide engineers to strengthen expertise in ML engineering
- Communicate AI/ML system behaviours, risks, and outcomes effectively to technical and non-technical stakeholders
- Collaborate with the Head of AI Labs to translate AI research and strategy into production-grade engineering solutions
Requirements
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field
- Proven ability to design and productionise retrieval-augmented generation (RAG) pipelines and agentic AI architectures
- Hands-on experience building agent-based AI solutions using orchestration frameworks (e.g. LangChain, Crew AI, etc)
- Expert programming skills in Python, with strong engineering discipline in testing, optimisation, CI/CD, and code quality
- Demonstrated success in developing, fine-tuning, and deploying ML/DL models using PyTorch and TensorFlow
- Experience integrating and scaling vector databases (Pinecone, Weaviate, Milvus)
- Expertise in cloud-native AI engineering, with deep delivery experience in AWS and working knowledge of Azure
- Proven ability to manage competing priorities and deliver robust, scalable, and ethical AI/ML solutions under tight timelines
Benefits
- Opportunity for professional growth and development
- Flexible working arrangements and hybrid work model
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
GU
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