At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.

What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.

Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.

Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.

Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!

About the Role:

The AVP, Data, Analytics & AI Engineering is the executive leader responsible for the strategic vision, architecture, development, and scaling of our enterprise data platforms and AI solutions. This individual will lead a team tasked with turning enterprise data assets into high-performance, compliant, and secure intelligence frameworks that drive automation and strategic decision-making across the entire company. The role bridges the gap between modern cloud data stack engineering and emerging AI paradigms (like LLMOps and Agentic workflows). This individual will ensure that Anaplan engineering standards drive direct, measurable business value while maintaining top-tier data security, governance and responsible AI practices.

Your Impact

This is a critical role that requires an executive and organizational leader with a high degree of enterprise transformation leadership, discretion, and the ability to lead multiple priorities in a fast-paced, sales-driven, SaaS environment. This individual will work directly with the CFO, CRO, CHRO, CIO and Product leaders while building a high-performance engineering team.

Key Responsibilities:

Create Advanced Analytics/Decision Intelligence driving predictive analytics, propensity, forecasting, experimentation, causal thinking, optimization.
GenAI/Agent Engineering that is essential to the enterprise agent strategy – MCP, RAG, embeddings/vector search, tool calling, agent architecture, evaluation, grounding, orchestration. Architect and govern the Enterprise Agentic AI Strategy, deploying multi-agent frameworks and LLM-powered tools at scale.
Architect and deploy enterprise-grade multi-agent AI systems for complex, multi-step workflows, integrating with ERP, CRM, and ITSM to automate high-value decisions end-to-end.
Design internal AI tools and agents (e.g., AI Finance Bot, domain-specific LLM applications) and lead the roadmap for next-generation agentic platforms as emerging capabilities mature.
Drive Data Governance & AI Readiness – quality, lineage, observability, catalog, access controls, PII, retention, AI data governance.
Provide business context to a Semantic & Context Architecture with metrics layer, business ontology, entity relationships, metadata, knowledge graphs/semantic models.
Scale the team – build, mentor, motivate and lead high-performance team across Data Engineering, Analytics Engineering and AI Engineering.
Partner collaboratively with business units, product teams, security, legal and compliance teams to deliver AI and data solutions that align to enterprise goals.
Drive Anaplan beyond pipelines feeding dashboards into a Modern Data Architecture environment.

Your Qualifications

Education: Bachelor’s or Master’s degree, Computer Science, Data Engineering, AI/ML, Math or a highly quantitative field of study.
Leadership experience of 12+ years in data and software engineering environments, with at least 5 years in a senior manager or executive role leading cross-functional teams.
Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).
Experience moving to modern data architecture environment, with Deep Datawarehouse/lakehouse (AWS Redshift, Databricks), streaming/batch, APIs, data products, ELT, CDC, structured + unstructured data experience.
Proven experience with