AVP, Data, Analytics & AI Engineering

About the role

Key responsibilities

• Drive advanced analytics and decision intelligence, including prediction, forecasting, experimentation, causal analysis, and optimisation.
• Architect and govern enterprise agentic AI strategy, including multi-agent frameworks, retrieval, embeddings, tool calling, evaluation, grounding, and orchestration.
• Deploy multi-agent systems for complex workflows integrated with ERP, CRM, and ITSM.
• Design internal AI tools and agents, and lead the roadmap for future agentic platforms.
• Lead data governance and AI readiness across quality, lineage, observability, cataloguing, access controls, PII, retention, and governance.
• Build semantic and context architecture covering metrics, business ontology, entity relationships, metadata, knowledge graphs, and semantic models.
• Build and lead Data Engineering, Analytics Engineering, and AI Engineering teams; partner with business, product, security, legal, and compliance.
• Drive a modern data architecture beyond dashboard-feeding pipelines.

Qualifications

• Bachelor's or master's degree in Computer Science, Data Engineering, AI/ML, Mathematics, or another highly quantitative field.
• 12+ years of data and software engineering leadership, including at least 5 years in a senior manager or executive role leading cross-functional teams.
• Strong familiarity with cloud data ecosystems such as Snowflake, Databricks, Vertex AI, or AWS SageMaker.
• Experience with modern data architecture, data warehouses or lakehouses, streaming and batch, APIs, data products, ELT, CDC, and structured and unstructured data.
• Proven production AI/ML engineering experience, including feature engineering, model serving, monitoring, and MLOps.
• Ability to communicate complex agentic systems, context engineering, and distributed database concepts to nontechnical and executive audiences.

About Anaplan