Executive Director, AI

Agency:

Hearts & Science

Job Function:

Media

Job Subfunction:

Media Planning and Buying

Job Description:

Role Purpose
Lead Hearts Uniteds AI and Automation team and own what we build why it matters and how approved opportunities move from technical definition to live solution. Reporting to the Chief Transformation Officer this role turns AI from potential into measurable value by delivering secure reliable and scalable agents automations and connected workflows.

Why This Role Matters

• Hearts United was built to challenge inertia and put Magnetism in a field shaped by platforms creators communities commerce culture and AI our advantage comes from discovering what others overlook daring to find the original way in and deciding like it matters.

• We believe media creativity is our advantage AI should be predictive and accountability should be measured through outcomes. This leader turns those beliefs into working intelligence that helps ambitious brands move faster manage complexity and maintain quality without proportional cost increases.

• Whatever the technology people work with people. The role must build AI that elevates human judgment extends expertise and gives teams more capacity for strategy creativity and growth.

The Leadership Mandate

• Own What We Build and Why: Set the technical portfolio make build versus reuse decisions and direct capacity to the highest-value opportunities.

• Lead the Builders: Direct solution architecture advanced coding prompt engineering integrations testing deployment and support.

• Automate Augment Productize: Make todays work faster change how work gets done and scale proven solutions when value demand and reliability are demonstrated.

• Build for Production: Move beyond prototypes through clear architecture acceptance criteria human oversight QA documentation monitoring and release controls.

Role Overview

This is the senior leader accountable for Hearts Uniteds AI and automation practice team and builds. Operations and Business Strategy own intake qualification prioritization and orchestration. This leader listens in as the technical authority assessing feasibility data readiness effort risk and reuse then takes accountability once an opportunity is approved for build.

The Chief Transformation Officer owns the broader transformation strategy operating model investment and enterprise tradeoffs. This leader owns technical direction solution quality delivery and day-to-day leadership of the AI and Automation team partnering with account teams product technology data operations legal and client stakeholders.

Key Responsibilities

AI Portfolio Architecture & Build Leadership

• Set the technical vision and roadmap for AI agents automations and connected intelligent workflows.

• Own decisions on architecture sequencing reuse configuration net-new build and productization.

• Lead solution design across agent architecture prompt systems orchestration APIs data pipelines authentication integrations and output experiences.

• Establish development standards reusable patterns shared prompt and component libraries documentation and responsible AI controls.

Team Leadership & Delivery Management

• Lead and develop the multidisciplinary team across AI solutions solutions engineering automation engineering data engineering QA deployment and support.

• Turn approved opportunities into actionable engineering briefs with requirements acceptance criteria data readiness success measures and named owners.

• Direct onshore nearshore and offshore delivery as one team using structured handoffs visible backlogs decision logs and release evidence.

• Manage capacity against the highest-value work while protecting quality reliability scalability and speed.

Solution Deployment & Oversight

• Lead the delivery lifecycle after approval: define design build validate deploy measure optimize repeat.

• Own build quality through code review prompt evaluation technical and expertise QA security and access controls and release decisions.

• Ensure every launch includes the documentation enablement monitoring and support needed to become part of the work.

• Prove contained use cases establish repeatable delivery and scale cross-account reuse and production support.

AI Engineering Talent & Capability Building

• Build a high-performing pipeline of AI engineering automation data and prompt engineering talent.

• Establish shared coding patterns prompt libraries reusable components peer review and technical documentation.

• Create clear ownership and a disciplined operating cadence across handoffs sprint reviews architecture gates releases and monthly value reviews.

Key Performance Indicators (KPIs)

• Production & Flow: Approved solutions moved into live workflows with predictable cycle time from technical definition to release.

• Quality & Reliability: Accuracy uptime defect rates response quality security and adherence to standards.

• Adoption & Value: Active usage hours released faster turnaround fewer errors improved decisions cost reduction and revenue enabled.

• Scale & Reuse: Solutions components prompts and integrations adopted beyond the original account or workflow.

• Team Health: Capability growth clear ownership documentation quality and delivery against roadmap commitments.

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Required Experience:

Director