The Director of Marketing Operations & AI is a senior leadership role that sits at the intersection of data, technology, and intelligent automation. You will be the operational backbone of GEP's marketing organization — responsible for funnel performance, marketing technology infrastructure, budget governance, and the deployment of AI agents that transform how the marketing team operates. This role requires both strategic vision and hands-on execution, with a mandate to eliminate inefficiency through intelligent systems, not just process.
RESPONSIBILITIES
- Marketing Funnel & Performance Analytics
- Own the full marketing funnel — track volume, velocity, conversion rates, and deal value at every stage, using AI-powered analytics to automatically surface trends and anomalies across industry, geography, and persona segments.
- Monitor LTV: CAC in real time — deploy agentic AI to continuously track customer lifetime value vs. acquisition cost by tactic, automatically flagging shifts and recommending budget reallocation before inefficiencies take hold.
- Deliver insights, not just metrics — run regular performance briefings for marketing, sales, and finance powered by AI-generated summaries that highlight what changed, why it matters, and what to do next — turning raw data into clear next steps.
- Build smart dashboards teams actually use — create and maintain AI-enhanced dashboards as the single source of truth for marketing performance, with intelligent alerts and natural-language querying so anyone can get answers without waiting on analysts.
Data, Analytics & Business Intelligence
- Own the design and delivery of GEP's marketing analytics infrastructure — ensuring consistent, trusted, and self-serve analytics is available to all marketing stakeholders
- Build and maintain a comprehensive marketing performance dashboard covering pipeline contribution, campaign ROI, channel efficiency, funnel health, and account engagement — accessible to CMO, Sales, and Finance
- Define and govern marketing KPIs and metrics taxonomy: standardize definitions, calculation logic, and KPI cadences across the organization so all teams are working from the same data
- Develop attribution models (first-touch, multi-touch, data-driven) that accurately reflect how marketing activities contribute to revenue, and communicate findings to sales and finance leadership
- Conduct deep-dive analysis on cohort behavior, buying journeys, and campaign performance to surface actionable insights — not just analyzing what happened, but explaining why and recommending what to do next
- Partner with data engineering or BI teams to ensure marketing data from all systems (MAP, CRM, web analytics, intent platforms, ad platforms) is cleanly integrated, normalized, and available in the data warehouse
- Leverage AI and predictive analytics to build forward-looking models: pipeline forecasting, lead quality scoring, churn risk indicators, and account propensity-to-buy signals
- Establish a regular analytics review cadence — weekly operational reviews, monthly performance readouts, and quarterly strategic reviews — with pre-built templates and commentary frameworks
- Ensure every metrics artifact is audience-appropriate: executive-level summaries for the CMO and board, tactical dashboards for campaign managers, and detailed drill-downs for ops and RevOps teams
AI Strategy, Agent Design & Deployment
- Define and lead GEP's AI strategy for marketing operations — identifying opportunities where AI agents can replace, streamline, or enhance existing workflows
- Design, build, and deploy AI agents to automate high-volume or repetitive marketing operations tasks, including lead scoring, data enrichment, campaign performance analysis, and content personalization workflows
- Manage the full lifecycle of AI agents in production: monitor performance, retrain or refine models/prompts, troubleshoot failures, and retire agents that no longer deliver value
- Create an AI agent governance framework — defining standards for agent ownership, SLA expectations, audit trails, and human-in-the-loop controls for critical decisions
- Collaborate with IT, data engineering, and external AI vendors to ensure agents are integrated securely with GEP's marketing and CRM systems
- Stay current with the evolving AI tooling landscape and proactively recommend new agentic capabilities (e.g., multi-agent orchestration, RAG pipelines, AI-native CRM features) that can benefit the marketing organization.
Process Design & Operational Excellence
- Design, document, and operationalize marketing processes that ensure data completeness, consistency, and reliability across all systems
- Apply AI-driven process transformation to collapse multi-step manual workflows into automated, intelligent pipelines — reducing cycle time and human error
- Champion simplicity: actively prevent customization bloat, over-engineered workflows, and redundant processes that slow the team down
- Lead change management for new process and technology rollouts — ensuring adoption through training, enablement, and feedback loops
- Build a culture of operational accountability within the marketing team, where every process has an owner and every data point has a defined source of truth
- Budget Administration & Financial Accountability
- Help prepare and administer the annual marketing budget, including planning, allocation, and real-time tracking of spend against plan
- Ensure marketing costs are coded and tracked correctly across systems, enabling accurate cost-per-lead, cost-per-opportunity, and ROI metrics by channel and tactic
- Provide finance and CMO with timely, accurate budget variance details and forecasts
- Use data to recommend budget reallocation toward highest-performing acquisition tactics
REQUIREMENTS
- 10–15+ years of experience in lead generation and marketing operations, including 8+ years of management experience
- Proven, hands-on experience in work process re-engineering — particularly leveraging AI and automation to transform, streamline, or collapse marketing operations activities
- Direct experience designing, building, and managing AI agents or AI-powered automation workflows in a production marketing environment
- Demonstrated experience building and managing a modern marketing technology stack at an enterprise software or SaaS company
- Proven track record in change management and organizational transformation
Technical Skills
- Deep proficiency with marketing automation platforms (Marketo, HubSpot, or equivalent) and CRM systems (HubSpot preferred)
- Hands-on experience with AI/ML tooling relevant to marketing: LLM APIs, AI agent frameworks (e.g., LangChain, Crew AI, or similar), prompt engineering, and agentic workflow design
- Strong understanding of data architecture, data pipelines, and system integrations (APIs, webhooks, iPaaS tools like Workato or Zapier)
- Expert-level proficiency with analytics and BI tools (e.g., Tableau, Looker, Power BI, or equivalent); ability to build and own dashboards independently without relying on a BI team
- Strong command of marketing attribution methodologies — first-touch, last-touch, multi-touch, and data-driven — and the ability to implement and explain them to senior stakeholders
- Experience working with data warehouses (Snowflake, BigQuery, or similar) and marketing data pipelines; comfort writing or reviewing SQL to validate and pull marketing data
- Familiarity with ABM platforms (6sense, Demandbase), CDP/data enrichment tools (ZoomInfo, Clearbit), and intent data
