Digital Marketing-Senior Manager

Verizon•Basking Ridge, NJ

4d•Hybrid

About The Position

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What you’ll be doing… As the Lead of Emerging Marketing Technology for Verizon Value, you will step into a highly technical product, operations, and marketing role that places you at the forefront of change at the intersection of marketing and AI. The role is responsible for leading the end-to-end design, deployment, and adoption of agentic AI workflows across the marketing lifecycle, acting as the critical bridge between marketing strategy and technical engineering teams to build closed-loop automation systems. Key responsibilities include executing the brand’s Generative and Answer Engine Optimization (GEO/AEO) roadmaps to maximize visibility across leading LLM platforms. Additionally, the position owns vendor procurement, technical architecture collaboration, and the governance frameworks necessary to mitigate adoption friction and ensure brand safety.

Requirements

Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
marketing with direct experience in marketing operations, campaign management, or martech.
Deep hands on building and customization tools and platforms in a marketing/business context.
Strong working knowledge of agentic AI and orchestration concepts: multi-agent workflows, RAG, prompt chaining, structured data/context engineering, how agents handoff tasks to one another.
Understanding of marketing data infrastructure - how briefs template, DAMs, campaign management tools, and performance/BI systems could feed into or receive output from AI agents.

Nice To Haves

MBA highly preferred.
Understanding of what makes a strong campaign brief and what data should inform it.
Experience with creative production workflows and the practical challenges of scaling creative and the practical challenges of scaling creative across many formats/channels.
Strong leadership and communication skills to drive recommendations, articulate tradeoffs, and communicate plans to senior executives.
Ability to translate complex ideas and express them in concise, simple to understand ways.
Strong project management skills, multi tasking is vital to success.
Leadership in digital space and strong knowledge of digital media platforms.
Demonstrated ability to direct and set strategy; follow through with execution.
Excels at working under pressure on multiple projects simultaneously while meeting deadlines with frequent interruptions and redefined priorities.
Proven ability to take initiative, influence others, and achieve results .
Skilled and comfortable at working within the marketing matrix.
Proven ability to manage a team of highly skilled marketeers.
Comfortable with continuously changing priorities.
Strong analytical, problem solving and planning skills.
Excellent written and verbal presentation skills.
Ability to easily transition from high level strategic thinking to detailed execution.

Responsibilities

Leading E2E design and roll out of AI tools to assist in campaign brief creations - systems that ingest brand guidelines, historical performance, audience data, and competitive context to draft or strengthen briefs and creative.
Architecting agentic workflows that can take and orchestrate downstream tasks - e.g. routing to creative scaling tools, triggering compliance/QA checks, populating media specs and naming.
Building AI-enabled scaling systems that take a hero asset and adapt it across formats (paid social, display, email, OOH, retail assets, etc.) and channels with minimal manual rework.
Owning roadmap for where in the campaign lifecycle AI tools provide the most leverage and sequence builds across the portfolio of brands.
Designing "human-in-the-loop" workflows that make creatives feel empowered by AI tools rather than replaced by them, actively solving for adoption friction.
Owning the execution of the GEO/AEO roadmap; monitor brand "citations" in LLMs, manage AI-readable schema, and turn the GEO strategy into actionable tactics for the SEO and affiliate team.
Partnering with data and analytics teams to design closed loop performance monitoring systems to surface in-flight campaign performance, identifying what’s working /underperforming and automatically feed learnings back into briefs, creative testing roadmaps, and optimization backlogs.
Defining technical architecture decisions in partnership with GTS/analytics; where orchestration logic lives, how brands campaign data feeds into agents, how outputs get reviewed before going live.
Being responsible for translating marketing requirements into technical user stories for data engineers, and vice versa.
Established guardrails, QA workflows, and brand safety/compliance review processes for AI-generated or assisted briefs and creative.
Building measurement frameworks proving ROI of AI tooling investments.
Creating training and enablement materials champion adoption across marketing teams.
Owning the evaluation, procurement, and ongoing lifecycle of third-party AI vendors and open-source models used in their orchestration pipelines.
Continuously scanning trends and translate them into a prioritized roadmap of what to pilot, monitor, and deprioritize (e.g. social commerce, AI commerce, etc.).
Aligning priorities with channel teams (e.g. performance marketing, media, SEO, social, PR) to design and structure pilots.
Building the case to scale winning pilots (tooling, playbooks, measurement) then hand off to the appropriate execution team.