AVP, Data, Analytics & AI Engineering

Overview

You lead the strategy and execution for Anaplan’s data platforms and AI solutions, turning data assets into secure, scalable intelligence. You guide architecture, governance, and cross‑functional collaboration to deliver business value through advanced analytics and agentic AI. Your role shapes enterprise data capabilities and modern AI practices at scale, in a fast-paced SaaS environment. You’ll partner with executive leaders to drive transformation and responsible AI adoption, while building a high‑performing team.

Responsibilities

• Create Advanced Analytics and Decision Intelligence for predictive analytics, forecasting, and experimentation
• Lead GenAI/Agent Engineering to support enterprise agent strategy (MCP, RAG, embeddings, tool calling, orchestration)
• Architect and govern Enterprise Agentic AI Strategy with multi-agent frameworks and large language model tools at scale
• Build enterprise-grade multi-agent AI systems for complex workflows and ERP/CRM/ITSM integrations
• Design internal AI tools and agent platforms and roadmap for next-generation capabilities
• Drive Data Governance and AI Readiness including data quality, lineage, observability, catalog, access controls, PII, retention
• Support Semantic & Context Architecture with metrics layer, ontology, metadata, and knowledge graphs
• Scale and lead a high-performance team across Data Engineering, Analytics Engineering and AI Engineering
• Collaborate with business units, security, legal, and compliance to align AI and data solutions with enterprise goals
• Advance Modern Data Architecture beyond dashboards to data pipelines and platforms

Key requirements

• 12+ years in data and software engineering with 5+ years in senior management or executive roles
• Strong familiarity with cloud data ecosystems (Snowflake, Databricks, Vertex AI, AWS Sagemaker)
• Experience modernizing data architectures (data warehouse/lakehouse, streaming/batch, APIs, ELT, CDC, structured and unstructured data)
• Proven ML/AI engineering experience with production deployment, feature engineering, model serving, monitoring, MLOps
• Ability to translate complex agentic systems and context-engineering into clear business narratives for executives
• Bachelor’s or Master’s degree in relevant quantitative fields

• executive leadership
• strong communication and storytelling to non-technical audiences
• cross-functional collaboration
• GenAI/Agent Engineering
• LLM-powered tools and multi-agent architectures
• Data governance and AI readiness

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