Assistant Vice President of Data, Analytics & AI Engineering

• 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
• 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
• 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

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

Experience moving to modern data architecture environment, with Deep Data warehouse/lakehouse (AWS Redshift, Databricks), streaming/batch, APIs, data products, ELT, CDC, structured + unstructured data experience

Exceptional ability to translate complex agentic systems, context-engineering strategies, and distributed database details into clear, business-relevant narratives for non-technical and executive boards

Proven experience with AI/ML engineering and success deploying ML models into production, feature engineering, model serving, monitoring, MLOps

Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker)

Education:

Bachelor’s or Master’s degree, Computer Science, Data Engineering, AI/ML, Math or a highly quantitative field of study