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Horizonmedia

VP, AI (Agentic Platforms & Transformation)

Salary$240k – $290k
LocationNew York, New York
Typefull-time
SeniorityVP
Experience12+ yrs
Company size80+ people
First seenOct 4, 2026 · 1w ago
Verified live5h ago
At a glanceSummarised by Seekless from the posting.
Must have7
12+ years of experience across AI, engineering, data, or technical product leadership
Proven track record of deploying AI-driven systems in enterprise environments
Strong understanding of LLM/agent architectures, orchestration patterns (RAG, tool use, multi-agent systems), and API-driven integrations
Experience making architecture decisions across AI platforms, including tradeoffs between RAG, direct API access, and hybrid approaches
Experience translating ambiguous business problems into scalable system architectures and production-grade AI solutions
Demonstrated ability to lead cross-functional teams and drive large-scale initiatives
Strong executive presence with the ability to influence senior stakeholders
Skills
LLM/agent architectures
RAG
tool use
multi-agent systems
API-driven integrations
BigQuery
MCP
Benefits
Health insurance
Life insurance
Disability insurance
Retirement savings plans
Unlimited PTO
Mental health wellness resources
Pet insurance
Childcare resources
Fertility assistance
Fitness reimbursement
Job Description
Position Summary
We are building an applied AI function focused on transforming how work gets done across the enterprise through agentic systems, workflow redesign, and intelligent data integration.
We are seeking a VP, AI to lead this transformation end-to-end.
This role owns how AI is identified, evaluated, built, and scaled within the organization’s workflows, moving from fragmented experimentation to a structured, repeatable system that delivers measurable business impact. You will operate across platforms, define how agents interact with enterprise systems and data, and establish the operating model required to scale adoption.
This is a systems leadership role requiring a balance of strategy, product thinking, and execution. You will translate ambiguous business problems into deployable solutions, drive platform and architecture decisions, and build the frameworks that embed AI into day-to-day operations.
Key Responsibilities
AI Strategy & Business Impact
•
Lead structured evaluation of AI platforms (e.g., Gemini, Claude, Perplexity), identifying strengths, limitations, and integration pathways
•
Translate platform capabilities and constraints into clear prioritization for enterprise-wide adoption
•
Identify and scale high impact use cases tied to measurable business outcomes
Agentic Platform & Workflow Ownership
•
Design and scale multi-step, agent-driven workflows that automate and augment core business processes
•
Translate complex, ambiguous workflows into structured, automatable systems
•
Ensure AI is embedded into core operations, not deployed as isolated tools
•
Establish reusable patterns to scale beyond one-off solutions
•
Drive consistency across teams while maintaining speed and flexibility
Enterprise Data & Integration Strategy
•
Define how third-party systems (SaaS platforms, databases, APIs) integrate into AI workflows
•
Establish scalable ingestion and integration patterns working with Infrastructure and Architecture Leadership throughout the organization (APIs, connectors, BigQuery, MCP, etc.)
•
Ensure data is structured, accessible, and governed for AI consumption
Adoption & Workflow Enablement
•
Own adoption of AI-driven workflows across the organization
•
Ensure all AI initiatives are tied to clear, quantifiable outcomes
•
Drive initiatives from POC → production → sustained usage
•
Define and track success metrics, including:
•
Workflow adoption
•
Time saved / efficiency gains
•
Throughput and decision velocity
•
Business impact (cost, revenue, productivity)
Measurement & Performance Ownership
•
Define and track success metrics across all AI initiatives, including:
•
Decision velocity improvements
•
Productivity and output lift
•
Establish baseline metrics prior to deployment and continuously measure post launch impact
•
Ensure all AI solutions are tied to clear, quantifiable business outcomes
Workflow Transformation & Operating Model
•
Redesign business processes to embed AI into daily operations
•
Establish and refine frameworks for intake, prioritization, and scaling of AI initiatives
•
Track engineering velocity, output, and impact across workstreams
Technical & Engineering Leadership
•
Build and lead a high-performing team of AI engineers and integration specialists
•
Establish standards for agent design, orchestration, and integration
•
Ensure high-quality execution across POCs and production systems
•
Partner with TPMs and engineering leadership to drive structured delivery
Cross-Functional Leadership
•
Act as the bridge between business, engineering, and platform teams
•
Present clear, opinionated recommendations to senior leadership
•
Drive alignment and best practices across the enterprise
•
Engage with external partners (e.g., Google) to accelerate innovation and influence roadmap direction
Qualifications & Experience
Required:
•
12+ years of experience across AI, engineering, data, or technical product leadership
•
Proven track record of deploying AI-driven systems in enterprise environments
•
Strong understanding of LLM/agent architectures, orchestration patterns (RAG, tool use, multi-agent systems), and API-driven integrations
•
Experience making architecture decisions across AI platforms, including tradeoffs between RAG, direct API access, and hybrid approaches
•
Experience translating ambiguous business problems into scalable system architectures and production-grade AI solutions
•
Demonstrated ability to lead cross-functional teams and drive large-scale initiatives
•
Strong executive presence with the ability to influence senior stakeholders
What Success Looks Like
•
AI is embedded into core workflows across the organization, not siloed tools
•
A repeatable system exists to move from idea → build → adoption → scale
•
Agents and workflows are reusable, scalable, and integrated into real operations
•
Enterprise data is governed, partitioned, accessible and usable in real time for AI-driven decision-making
•
AI initiatives consistently deliver measurable business impact at scale
What Great Looks Like
•
Brings clear, structured recommendations, not open-ended questions
•
Translates complex workflows into scalable systems, not one-off solutions
•
Makes strong platform and architecture decisions with clear tradeoffs
•
Balances speed (POCs) with long-term scalability
•
Operates with full ownership across strategy, execution, and outcomes
Legal
Horizon Media is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Salary Range
$240,000.00 - $290,000.00
A successful applicant’s actual base salary may vary based on factors such as individual’s skill sets, experience, training, education, licensure/certifications, and qualifications for the role. As an organization, we take an aptitude and competency-based hiring approach. We provide a competitive total rewards package including a discretionary bonus and a variety of benefits including health insurance coverage, life and disability insurance, retirement savings plans, company paid holidays and unlimited paid time off (PTO), mental health and wellness resources, pet insurance, childcare resources, identity theft insurance, fertility assistance programs, and fitness reimbursement.
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