Asks for

The ad says“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.”
The ad says“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.”
The ad says“Scale the team – build, mentor, motivate and lead high-performance team across Data Engineering, Analytics Engineering and AI Engineering.”
The ad says“Proven experience with AI/ML engineering and success deploying ML models into production, feature engineering, model serving, monitoring, MLOps.”
The ad says“Scale the team – build, mentor, motivate and lead high-performance team across Data Engineering, Analytics Engineering and AI Engineering.”
The ad says“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.”
The ad says“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.”
The ad says“Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).”
The ad says“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.”
The ad says“Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).”
The ad says“Scale the team – build, mentor, motivate and lead high-performance team across Data Engineering, Analytics Engineering and AI Engineering.”
The ad says“Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“Provide business context to a Semantic & Context Architecture with metrics layer, business ontology, entity relationships, metadata, knowledge graphs/semantic models.”
The ad says“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.”
The ad says“Proven experience with AI/ML engineering and success deploying ML models into production, feature engineering, model serving, monitoring, MLOps.”
The ad says“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.”
The ad says“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.”
The ad says“Provide business context to a Semantic & Context Architecture with metrics layer, business ontology, entity relationships, metadata, knowledge graphs/semantic models.”
The ad says“Provide business context to a Semantic & Context Architecture with metrics layer, business ontology, entity relationships, metadata, knowledge graphs/semantic models.”
The ad says“Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).”
The ad says“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.”
The ad says“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.”
The ad says“Strong familiarity with core technical stack - cloud data ecosystems (eg. Snowflake, Databricks, Vertex AI, AWS Sagemaker).”

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

Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)

We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation. 

Fraud Recruitment Disclaimer 

It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.  

Anaplan does not: 

Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.  
Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.

All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.  

Privacy & AI Notice

Candidate data processed during our recruitment activities is handled in accordance with our Candidate Privacy Notice. This may include the use of artificial intelligence or automated tools to assist our team in evaluating qualifications.