Director, Product Management GenAI Digital Media

Clarvos LLC•Charleston, SC

8d•Remote

About The Position

The Director of Product Management - GenAI Digital Media will define, build, and scale Clarvos' generative AI products for the creation, adaptation, validation, management, and activation of commercial image and video assets. This leader will own the product vision and end-to-end roadmap for AI-powered creative applications that enable marketers and agencies to produce high-quality, brand-aligned, platform-ready advertising assets with greater speed, scale, and performance. This role requires a proven 0-to-1 product builder who has personally owned the development and production deployment of generative AI video and image products used for marketing, advertising, or commercial creative workflows. The ideal candidate combines deep AdTech and MarTech knowledge with practical fluency in multimodal generative AI, creative-production systems, model evaluation, asset pipelines, and advertiser workflows. They must be comfortable working directly with model outputs, APIs, prototypes, data, and technical documentation - not operating solely through strategy or delegation. The Director will lead cross-functional execution across Product, Engineering, Applied AI/ML, Design, Creative, Data, Legal, Privacy, Security, Customer Success, Sales, and Marketing. This leader will be accountable for turning emerging AI capabilities into commercially viable products that create measurable customer value, improve creative quality and campaign outcomes, and establish a differentiated digital-media platform for Clarvos.

Requirements

10 or more years of product management experience, including significant leadership experience building technical, AI/ML, creative-technology, AdTech, MarTech, media, or enterprise SaaS products.
Demonstrated end-to-end ownership of generative AI video application that progressed from concept or prototype to a production product used for commercial marketing or advertising.
Proven 0-to-1 product leadership, including opportunity definition, customer discovery, business case development, technical scoping, prototype validation, launch, commercialization, and scale.
Hands-on experience evaluating and using generative AI models, APIs, creative tools, and prototypes across image and video modalities.
Strong practical understanding of multimodal generative AI, including diffusion or transformer-based generation, text and image conditioning, embeddings, model adaptation, inference, orchestration, and evaluation.
Ability to work credibly with engineers and applied scientists on model capabilities, architecture, APIs, data pipelines, latency, reliability, cost, quality, and production tradeoffs.
Deep understanding of commercial image and video production workflows, including concepting, storyboarding, editing, compositing, motion, audio, rendering, resizing, localization, review, approval, and delivery.
Strong understanding of digital advertising and marketing workflows, creative formats, campaign objectives, advertiser and agency needs, publisher specifications, asset trafficking, experimentation, and performance measurement.
Experience defining quantitative and qualitative evaluation systems for generative outputs and distinguishing visually impressive demonstrations from reliable, repeatable, commercially usable products.
Experience building products that incorporate brand controls, creative templates, asset metadata, product catalogs, rights and permissions, approval workflows, and enterprise governance.
Experience with responsible AI, content safety, intellectual-property and likeness risks, provenance, data governance, and brand-safety requirements for commercial creative applications.
Proven ability to write precise product requirements, technical specifications, decision documents, launch plans, success metrics, and executive communications.
Experience leading cross-functional teams across Product, Engineering, Applied Science, Data, Design, Creative, Legal, Privacy, Security, Sales, Marketing, and Customer Success.
Strong business judgment and experience connecting product investment to revenue, adoption, retention, gross margin, customer value, and measurable advertising outcomes.
Demonstrated ability to operate as a self-starter, create structure in ambiguity, make high-judgment tradeoffs, and maintain accountability through production launch and ongoing operation.
Bachelor's degree in computer science, engineering, design, media technology, business, marketing, or a related field, or equivalent practical experience.

Nice To Haves

Experience building advertiser-facing generative creative tools at an advertising platform, DSP, publisher, creative technology company, agency platform, or enterprise marketing-technology provider.
Experience with leading image and video generation ecosystems, model providers, or creative platforms and with integrating model APIs into production applications.
Experience with agentic creative workflows, prompt orchestration, model routing, retrieval-augmented generation, fine-tuning, LoRA or similar adaptation techniques, and human-in-the-loop systems.
Experience with video-specific technologies such as shot planning, temporal consistency, motion control, lip synchronization, voice, audio generation, captions, scene extension, and automated editing.
Experience with digital asset management, content supply chains, creative automation, dynamic creative optimization, product feeds, brand systems, or campaign-management platforms.
Working knowledge of SQL, API tools, notebooks, analytics platforms, or other environments used to inspect model behavior, evaluate outputs, troubleshoot workflows, and validate product performance.
Experience establishing model-quality benchmarks, annotation programs, human evaluation, red-team testing, online experimentation, and production monitoring for generative AI systems.
Familiarity with C2PA or comparable content-provenance standards, watermarking, disclosure practices, copyright and licensing considerations, and emerging AI regulations.
Experience building or managing teams in a high-growth environment where technical curiosity, speed, creative judgment, and hands-on product execution are critical.

Responsibilities

Own the product vision, strategy, investment thesis, and multi-year roadmap for generative AI image, video, and multimodal creative products serving advertisers, agencies, and internal creative teams.
Lead products from zero-to-one discovery and prototyping through model selection, technical architecture, beta, production launch, commercialization, adoption, and continuous optimization.
Define AI-powered workflows for text-to-image, image-to-image, text-to-video, image-to-video, video extension, editing, resizing, localization, background generation, product placement, variant creation, and multi-format campaign adaptation.
Build advertiser-facing experiences that translate a brand, product catalog, campaign objective, audience, channel, and creative brief into commercially usable digital assets and campaign-ready variants.
Create product capabilities that support the full creative lifecycle, including ideation, storyboarding, generation, editing, review, approval, versioning, storage, metadata, rights management, publishing, measurement, and reuse.
Personally review model capabilities, APIs, prototypes, prompts, workflows, and generated outputs; use hands-on experimentation to evaluate feasibility, creative quality, failure modes, and customer value before committing roadmap investment.
Partner with Applied AI/ML and Engineering to define model requirements, training and evaluation data, inference architecture, orchestration, fine-tuning or adaptation approaches, model routing, latency, scalability, reliability, and unit economics.
Determine when to build proprietary capabilities, fine-tune or adapt open models, integrate third-party model providers, or combine multiple models and tools into a differentiated product experience.
Define model and product evaluation frameworks for visual quality, temporal consistency, motion quality, prompt adherence, brand fidelity, product accuracy, human realism, text rendering, diversity, controllability, editability, safety, and commercial usability.
Establish a rigorous creative quality bar and partner with Design and Creative leaders to translate visual craft, storytelling, composition, pacing, brand standards, and advertising effectiveness into repeatable product requirements and machine-readable evaluation criteria.
Build scalable brand-intelligence and asset-control capabilities, including brand kits, style references, product truth, approved claims, color and typography constraints, logos, visual identities, reusable templates, and campaign-specific creative rules.
Develop workflows for synthetic focus groups, creative scoring, ranking, pre-launch validation, and performance feedback so that generated assets can be evaluated and improved before and after media activation.
Connect creative generation to AdTech activation workflows across social, search, display, mobile, retail media, CTV, online video, native, and other publisher formats, including platform-specific dimensions, durations, file limits, safe zones, and policy requirements.
Partner with Campaign Execution, Audience Intelligence, Measurement, and publisher-integration teams to ensure generated assets can be targeted, trafficked, tested, measured, optimized, and learned from across the campaign lifecycle.
Define product requirements, technical specifications, data contracts, user journeys, acceptance criteria, quality thresholds, edge cases, launch criteria, and operating procedures for complex AI and digital-asset capabilities.
Own product testing and launch readiness, including model-output review, API validation, end-to-end workflow testing, performance benchmarking, safety evaluation, regression testing, and production monitoring.
Build feedback loops that connect creative inputs, model behavior, human review, campaign delivery, engagement, conversion, and business outcomes to improve future asset generation and recommendation quality.
Define and manage product economics, including generation cost, inference cost, storage and rendering cost, vendor spend, gross margin, cost per accepted asset, and the tradeoffs among quality, speed, and scale.
Partner with Legal, Privacy, Security, and Brand Safety teams to establish requirements for intellectual-property risk, rights and licensing, consent, likeness, prohibited content, provenance, disclosure, watermarking, data governance, and responsible AI.
Engage directly with advertisers, agencies, creative teams, and commercial stakeholders to understand production constraints, validate product concepts, prioritize use cases, and accelerate adoption.
Build, lead, and develop a high-performing product team and create strong operating mechanisms across Product, Engineering, AI/ML, Design, Creative, and go-to-market functions.
Communicate product strategy, technical tradeoffs, investment needs, quality risks, roadmap progress, launch readiness, adoption, and business impact clearly to executive leadership and cross-functional stakeholders.