AVP, Data, Analytics & AI Engineering

About Anaplan

About the Role

Key Responsibilities

• Drive advanced analytics and decision intelligence, including prediction, propensity, forecasting, experimentation, causal thinking, and optimization.
• Architect and govern enterprise agentic AI strategy, including multi-agent frameworks and LLM-powered tools.
• Deploy enterprise multi-agent AI systems for complex workflows integrated with ERP, CRM, and ITSM.
• Design internal AI tools and agents and lead roadmaps for next-generation agentic platforms.
• Drive data governance and AI readiness across quality, lineage, observability, catalogs, access, PII, retention, and responsible AI.
• Develop semantic and context architecture, including metrics, ontologies, entity relationships, metadata, knowledge graphs, and semantic models.
• Build and lead teams across Data Engineering, Analytics Engineering, and AI Engineering.
• Partner with business units, product, security, legal, and compliance teams on enterprise data and AI solutions.
• Advance the company's data architecture beyond pipelines that feed dashboards.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, AI/ML, Mathematics, or a highly quantitative field.
• 12+ years of leadership in data and software engineering, including 5+ years in senior management or executive roles leading cross-functional teams.
• Familiarity with cloud data ecosystems such as Snowflake, Databricks, Vertex AI, or AWS SageMaker.
• Experience with modern data architecture, warehouse or lakehouse systems, streaming and batch, APIs, data products, ELT, CDC, and structured and unstructured data.
• Production AI/ML engineering experience spanning model deployment, feature engineering, serving, monitoring, and MLOps.
• Ability to translate complex agentic systems, context engineering, and distributed database details into business-relevant narratives for executive and non-technical audiences.