Marketing Operations & AI Strategist
raleigh, NC, 27703
Reference ID: 32445061
Date Posted: 06/12/2026
Job Title: Marketing Operations & AI Strategist
Location-Type: Remote (must reside in one of the following states: AL, AR, AZ, CA, CO, CT, DE, FL, GA, IL, IN, KY, MD, MI, MN, MO, NC, NH, NJ, NY, OH, OR, PA, SC, TN, TX, UT, VA, VT, WA)
Start Date: ASAP
Duration: Permanent
Compensation Range: $180,000 - $200,000 plus 15% Bonus
Benefits: Medical (PPO and HDHP options via Client, including HSA with company contributions), Dental and Vision, FSA and Dependent Care Account, company-paid Life Insurance, STD and LTD, voluntary benefits (Supplemental Life, Critical Illness, Accident, Pet Insurance), 401(k) with up to 3% employer match and no vesting period, Flexible PTO, 10 company holidays, Parental Leave, Paid Volunteer Time Off, Employee Reimbursement Program (well-being, technology, or professional development). Annual performance bonus of 15%.
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
The client is seeking a hands-on Marketing Operations & AI Strategist to architect and execute an AI-native transformation of the marketing function, owning both the strategic vision and the technical build across HubSpot, Salesforce, and adjacent GTM systems.
Job Summary
Define and execute the organization's AI strategy for marketing, designing and deploying AI-powered workflows, agents, and decision systems tied to measurable pipeline and revenue outcomes.
Architect scalable marketing operations infrastructure across HubSpot, Salesforce, and related GTM tools, partnering with GTM Engineering on integrations and data flows.
Build next-generation attribution models and AI-driven reporting systems that connect marketing activity to pipeline and revenue performance.
Own lifecycle strategy and implementation, including intelligent lead scoring, routing, segmentation, and nurture using behavioral and firmographic data.
Build a repeatable, scalable campaign operating system with standardized frameworks, templates, and QA processes.
Eliminate manual and fragmented processes through automation and AI, replacing them with intelligent, optimized workflows.
Drive adoption of new tools, systems, and ways of working across Marketing, Sales, GTM Ops, and Leadership, mentoring team members and elevating overall operations maturity.
Minimum Requirements:
10 years of experience in Marketing Operations, Growth Operations, or Marketing Analytics within a B2B SaaS environment.
Expert-level HubSpot proficiency (3-5 recent years) spanning campaign architecture, attribution, reporting, lead scoring, segmentation, and Salesforce integrations.
Strong Salesforce expertise and deep understanding of marketing technology ecosystems, data architecture, APIs, integrations, and funnel analytics.
Proven track record building, scaling, and optimizing marketing operations functions and systems from the ground up in a hands-on individual contributor capacity.
Hands-on experience deploying AI into production marketing workflows using tools such as Claude, ChatGPT, Gemini, AI agents, prompt engineering, and workflow automation.
Demonstrated ability to connect AI initiatives to measurable business outcomes including pipeline growth, revenue impact, and operational efficiency.
Strong business acumen with the ability to translate complex data into clear, strategic recommendations for senior leadership.
Preferred Qualifications:
Experience building an AI-first marketing operations function from the ground up, including designing or managing AI agents or autonomous workflows in a production environment.
Demonstrated ability to maintain code bases for technical marketing systems such as lead scoring models.
Background in high-growth or transformation-stage SaaS companies with a track record of rebuilding attribution in complex GTM environments.
Experience leading change management initiatives tied to the introduction of new technologies and Client operational approaches.
Familiarity with development and architecture best practices and comfort working with APIs and debugging complex, multi-system integrations.
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