Director, Marketing Tech & AI Transformation

Early Warning; San Francisco (CA); Hybrid; USD 186,000 - 210,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Match

Paid Time Off

Parental Leave

Family Planning Support

Job summary

Early Warning seeks a Director of Marketing Technology and Transformation to lead the Marketing Operations tech agenda and drive AI-enabled transformation across brands such as Zelle, Paze, and Certos. This role partners with Technology, Data, Legal, Risk, and Compliance to deliver impactful solutions.

The role focuses on a network-first approach, reusable platforms, and responsible AI deployment to boost speed, quality, and capacity while aligning with regulatory requirements.

Qualifications

• Bachelor's degree or equivalent combination of education and relevant experience.
• Typically 12+ years of experience in marketing technology, marketing automation, or related disciplines.
• Proven ability to develop multi-year strategies, roadmaps, and executive recommendations for complex portfolios.
• Demonstrated leadership of cross-functional teams and enterprise transformation initiatives.

Responsibilities

• Own and maintain Marketing’s multi-year MarTech roadmap across brands.
• Set priorities for technology improvements with a network-first approach.
• Develop business cases and funding recommendations for major technology investments.
• Lead efforts to map and improve marketing processes with automation and AI.
• Define transformation success measures and track adoption and outcomes.

Skills

Strategic leadership

Stakeholder management

Communication

AI governance

Education

Bachelor's degree or equivalent

Tools

CRM Systems

Job description

Early Warning seeks a Director of Marketing Technology and Transformation to lead the Marketing Operations tech agenda and drive AI-enabled transformation across brands such as Zelle, Paze, and Certos. This role partners with Technology, Data, Legal, Risk, and Compliance to deliver impactful solutions.

The role focuses on a network-first approach, reusable platforms, and responsible AI deployment to boost speed, quality, and capacity while aligning with regulatory requirements.