About this role
Leading the strategic vision and architecture of enterprise data platforms and AI solutions, the AVP, Data, Analytics & AI Engineering spends their days bridging modern cloud data stack engineering with emerging AI paradigms. The chosen leader builds and scales high-performance teams across data engineering, analytics engineering, and AI engineering while collaborating directly with executive stakeholders like the CFO, CRO, CHRO, and CIO. Operating within a fast-paced, sales-driven SaaS environment, the team turns enterprise data assets into secure intelligence frameworks that automate decision-making across the company.
This executive role exists to drive Anaplan beyond traditional pipelines feeding dashboards and into a modern data architecture environment. The incoming leader architects the enterprise agentic AI strategy, deploying multi-agent frameworks, LLM-powered tools, and semantic models at scale while maintaining top-tier data governance and security. A strong candidate is an enterprise transformation leader who combines deep technical expertise in distributed data and AI systems with the communication skills needed to translate complex strategies into business narratives for executive boards.
What you will do
- Design advanced analytics and decision intelligence capabilities that drive predictive analytics, propensity modeling, forecasting, experimentation, and optimization.
- Architect and govern an enterprise agentic AI strategy by deploying multi-agent frameworks and LLM-powered tools at scale.
- Deploy enterprise-grade multi-agent AI systems for complex, multi-step workflows that integrate with ERP, CRM, and ITSM platforms.
- Drive comprehensive data governance and AI readiness covering data quality, lineage, observability, cataloging, access controls, and privacy.
- Provide business context to a semantic and context architecture featuring metrics layers, business ontology, knowledge graphs, and semantic models.
- Build, mentor, and lead a high-performance team spanning data engineering, analytics engineering, and AI engineering.
- Partner collaboratively with business units, product teams, security, legal, and compliance teams to deliver aligned solutions.
What you need
- Hold a Bachelor's or Master's degree in Computer Science, Data Engineering, AI/ML, Mathematics, or a highly quantitative field.
- Bring 12 or more years of leadership experience in data and software engineering environments.
- Possess at least 5 years of experience in a senior manager or executive role leading cross-functional teams.
- Demonstrate strong familiarity with core technical stacks including cloud data ecosystems such as Snowflake, Databricks, Vertex AI, and AWS Sagemaker.
- Show proven experience moving organizations to modern data architecture environments with deep data warehouse or lakehouse, streaming, and API integration experience.
- Exhibit proven experience with AI/ML engineering, model serving, monitoring, MLOps, and successful production deployments.
- Display an exceptional ability to translate complex agentic systems and distributed database details into clear narratives for executive boards.
Skills and tech stack
Questions candidates ask
What level of leadership experience is required for this position?
Candidates must have 12 or more years of leadership experience in data and software engineering environments, with at least 5 years in a senior manager or executive role leading cross-functional teams.
What educational background is expected?
A Bachelor's or Master's degree in Computer Science, Data Engineering, AI/ML, Mathematics, or a highly quantitative field of study is required.
Which executives will this role work with directly?
This individual will work directly with the CFO, CRO, CHRO, CIO, and Product leaders while building a high-performance engineering team.