Overview

Director, Data Science & AI Engineering

Responsibilities

• Cvent’s AI Engineering & Data Science function is the engine that translates data into production intelligence — commercial models, agentic workflows, NLQ interfaces, and AI systems operating at scale across a B+ global SaaS business. We are hiring a Director to own it.
• This is an enterprise leadership role with a dual mandate: operational excellence and strategic thought leadership. You own the corporate AI portfolio end-to-end — delivery, architecture governance, cross-functional stakeholder relationships, and long-term direction. You lead the AI Centre of Excellence, shaping how Cvent thinks about, builds, and governs AI as a business-critical capability.
• The right person is a decisive, dynamic leader with 15+ years in AI and data science — operationally rigorous enough to run a complex multi-workstream function, and commercially credible enough to influence C-suite and board-level conversations. As comfortable in a strategy session as in an architecture review.
• Run a multi-workstream AI and data science function with the discipline a $B+ enterprise demands — predictable delivery, zero stakeholder surprises, quality as the baseline.
• Bring deep domain expertise to GTM projects and corporate use cases across Sales, Marketing, Revenue Operations, Customer Success, Finance, and Tech/IT — ensuring AI/ML solutions are designed with the business context they will operate in, not just the data available.
• Partner actively with business leaders and function heads to shape the future AI agenda — co-developing roadmaps, surfacing high-leverage opportunities, and ensuring the team’s work is connected to Cvent’s most important growth and operational priorities.
• Own the operating model: delivery cadences, capacity management, cross-functional dependencies, intake and prioritization, and executive reporting.
• Set and enforce engineering standards across the portfolio: experiment tracking, model versioning, ML CI/CD, observability, and documentation — across internal teams and external partners.
• Own Cvent’s enterprise AI portfolio — spanning commercial AI, marketing intelligence, operational automation, financial governance, and agentic systems — accountable for roadmap, delivery, and measurable business outcomes.
• Set AI investment priorities at the corporate level: allocate capacity, sequence initiatives by strategic value, and make explicit trade-offs across competing demands in partnership with senior leadership.
• Govern the AI technology stac k: model registry, orchestration layer, observability infrastructure, and data contracts. All production systems meet enterprise-grade standards for reliability, explainability, and auditability.
• Define and evolve the AI CoE charter — establishing its mandate as an enterprise capability function focused on continuously improving the team’s core AI and data science capabilities, strengthening data strategy, and raising the security posture of all AI systems in production.
• Define the paved road for AI — reusable patterns, approved tooling, and delivery standards that enable teams to build with speed and confidence while maintaining a reach-oriented posture: scanning the external AI landscape and updating guidance before the business asks for it.
• Translate the CoE’s work into executive narratives for C-suite and board — connecting capability investment to business value and help position Cvent as an AI-native enterprise.
• Lead a team of Data scientists, and AI engineers — owning hiring, performance management, career architecture, and succession planning at Director level.
• Set a high-performance standard and hold it. Develop strong leaders within the team. Address under performance directly, constructively, and decisively.
• Build institutional resilience: reduce key-person dependency through structured knowledge transfer, role design, and a talent pipeline that scales with Cvent’s AI ambitions.
• Serve as Cvent’s senior AI voice across Marketing, Sales, RevOps, CS, Product, Finance, and Technology — owning the relationship between AI capability and business demand at the most senior level.
• Engage C-suite and business function heads as a strategic partner: presenting portfolio outcomes, advising on competitive AI strategy, and translating the function’s work into language that drives decisions.
• Communicate proactively on strategy, delivery status, risks, and results. Credibility is built on consistency of delivery and sharpness of insight.

Qualifications

• 15+ years in AI/ML engineering, data science, or enterprise analytics — with a sustained Director-level track record owning large-scale, multi-workstream AI portfolios.
• Demonstrated experience building or leading an AI Centre of Excellence or enterprise-wide AI capability in a complex, global B2B or SaaS environment.
• Proven ability to engage C-suite and board-level stakeholders on AI strategy and investment — with the executive presence to influence without authority.
• Deep experience delivering commercial AI across GTM and corporate functions at enterprise scale: NLQ, personalization, propensity modelling, intelligent automation, and production-grade AI systems.
• Authoritative in LLM architecture, RAG/NLQ design, ML lifecycle governance, and enterprise AI observability. Engages as a peer with principal engineers on design decisions and platform trade-offs.
• Strong command of Snowflake, Databricks, and Python-based AI engineering. Understands how data architecture and security choices shape the reliability and scalability of AI systems downstream.
• Operationally exceptional: runs complex, multi-team functions with clarity, discipline, and predictability at enterprise scale.
• Executive communicator: translates AI complexity into business value for C-suite audiences and business strategy into engineering direction for technical teams. Crisp, direct, proactive.
• Dynamic and high-conviction: shapes the agenda rather than responds to it, decides with incomplete information, holds the organization to a high standard of both ambition and execution.
• Reach-oriented thought leader: monitors the external AI landscape continuously, forms a point of view fast, and brings it into the organization before the business asks for it.
• Enterprise-grade AI delivery across GTM and corporate functions — commercially impactful, architecturally sound, and trusted by senior leadership as a strategic asset.
• A CoE with a defined charter, a living paved road, and a team with measurably stronger core capabilities, data strategy maturity, and AI security posture.
• C-suite and business function heads who engage this Director proactively on AI strategy — treating the function as a competitive differentiator, not a support service.
• A high-performing organization with leadership depth, reduced key-person risk, and a talent pipeline ready to scale.