VP, AI Solutions & Product Delivery

Lionsgate•Santa Monica, CA

2d•$250,000 - $300,000•Onsite

About The Position

Lionsgate is seeking a high-agency, hands-on AI product builder to create and ship internal products that materially improve how teams across the business work. This role will own strategic priorities and business problems from stakeholder handoff through design, build, deployment, adoption, and continuous improvement. The mandate is to bring the resourcefulness, technical creativity, and delivery discipline of a startup to an established media company. The ideal candidate has built and shipped products in a startup, early-stage, or similarly fast-moving environment and is excited by the challenge of bringing meaningful change to a traditional business. They translate ambiguity into working software, iterate with users in short cycles, and pair urgency with patience and sound organizational judgment. They build trust across functions, understand that durable change requires adoption as well as technology, and bring enough media experience to understand the business cases and customers behind the work.

Requirements

6+ years of experience building and shipping software products, including meaningful experience in a startup, early-stage company, new venture, or comparable zero-to-one environment.
A track record of personally taking multiple products from ambiguous need through production launch, user adoption, and continued iteration; not solely to prototype or proof-of-concept.
Strong hands-on software-development capability, including proficiency with modern web or application frameworks, Python and/or JavaScript/TypeScript, APIs, cloud services, data integrations, AI models, and automation tools.
Strong product judgment and a demonstrated ability to reduce scope intelligently, make fast decisions with incomplete information, and balance speed, user value, technical quality, and risk.
Meaningful experience in media, entertainment, or a closely related content business, with an understanding of the workflows, economics, and customer needs that shape practical use cases.
The patience, resilience, communication skills, and organizational judgment to build trust, influence senior stakeholders, and sustain change within a complex, established institution.

Nice To Haves

Experience as a founding engineer, technical founder, early product engineer, or similarly broad hands-on builder.
Experience building AI-native products or working within an AI startup or high-growth product organization.
Experience developing internal applications, knowledge systems, decision-support tools, or workflow products for nontechnical users.
Experience deploying generative AI in environments with meaningful security, privacy, intellectual property, or compliance considerations.
Experience establishing a faster product-development practice inside a larger or more process-heavy organization.

Responsibilities

Own AI-enabled internal products from initial stakeholder handoff through discovery, scoping, build, deployment, adoption, and ongoing improvement.
Personally design, code, integrate, and deploy functional products using AI models, APIs, modern application frameworks, automation platforms, cloud services, and enterprise data sources.
Translate ambiguous needs into clear requirements and working software; right-size scope, test early, and ship useful increments in short, accountable cycles.
Use executive sponsorship and technical credibility to clarify tradeoffs, question assumptions constructively, surface blockers, and help cross-functional teams reach timely decisions.
Own the path from prototype to production, building effective partnerships with Engineering, Data, Cybersecurity, IT, Legal, and other teams to meet enterprise requirements while maintaining momentum.
Prioritize opportunities based on business value, feasibility, risk, user readiness, and time to impact; make pragmatic build-versus-buy decisions and stop low-value work quickly.
Partner directly with media and corporate stakeholders throughout development, learning their workflows and customers, managing feedback, testing, launch, and adoption, and measuring business value.
Create lightweight, durable documentation, support models, and reusable technical patterns so products remain reliable while future builds move faster.