Senior Director, Technical Product Management, Content Engineering and Intelligence

Paramount•San Francisco, CA

2d•Onsite

About The Position

WeAreParamount is on a mission to unleash the power of content. We have the brands, the stars, and the power to entertain the planet. Paramount Streaming is seeking a Senior Director of Technical Product Management to lead the product strategy and execution, guiding the direction of Content Engineering & Intelligence within Paramount’s global streaming ecosystem. This leader will guide the vision and strategy for important content systems, focusing on improving metadata quality and content knowledge, managing the creation of embedding generation, short-form content workflows, and reusable content services for Paramount+ and Pluto TV. This role covers content metadata and feature pipelines, content data engineering, canonical content systems, embedding and enrichment pipelines, short-form content engineering workflows, and machine learning capabilities, with an emphasis on content services platforms to enhance internal user experiences and improve platform features for discovery, personalization, search, experimentation, and new AI-powered content experiences. You will work closely with content engineering, applied ML, platform engineering, data science, product, design, operations, and the executive team to ensure our content foundations are scalable and reliable, supporting the next generation of AI-driven streaming experiences. This is a highly strategic and deeply technical executive role responsible for how content becomes a durable strategic asset across Paramount Streaming.

Requirements

10+ years of experience in product management, technical product management, or equivalent product executive team roles.
5+ years leading technical product areas in content platforms, metadata systems, AI/ML infrastructure, content intelligence, data platforms, or adjacent domains.
Experience leading PMs or complex technical product areas across engineering, ML, data, design, operations, and business teams.
Experience in delivering large content platforms, including metadata systems, internal tools, data platforms, and machine learning systems, in streaming, media, consumer technology, or AI-focused companies.
Technical fluency across data systems, content pipelines, APIs, internal tools, metadata systems, and ML-enabled platforms.
Experience with content metadata systems, including enrichment workflows and canonical metadata models, content identifiers, taxonomy, ontology, and content normalization methods.
Experience with data pipelines, feature stores, datasets ready for models, batch and near-real-time architectures, MLOps, monitoring, and experimentation systems.
Fluency with data analysis workflows, including SQL, Python, telemetry, data quality signals, instrumentation, and platform health metrics.
Executive communication skills, with the ability to translate technical platform work into business impact, strategic tradeoffs, and clear decision-making.
Ability to align engineering, ML, design, operations, product, and business stakeholders across matrixed organizations.

Nice To Haves

Experience in building or improving content intelligence capabilities, including personalization and recommendations, search, short-form content, content discovery, advertising, and other large-scale consumer AI systems.
Familiarity with embedding generation, vector-based content representation, vector databases, asset-level and title-level content intelligence systems, and downstream ML readiness.
Experience with applied ML systems used in content transformation, understanding, tagging, enrichment, short-form generation, or content optimization.
Experience linking content systems from the beginning to systems that manage ranking, recommendation, search, personalization, experimentation, and short-form use cases at the end.
Product intuition for internal tools and platform services, including adoption, usability, self-service workflows, documentation, and API design.
Experience balancing technical complexity, platform reuse, tooling UX, content quality, workflow efficiency, and delivery velocity.
Hands-on technical fluency with coding tools such as Python, SQL, IDEs, GitHub, notebooks, dashboards, and developer workflows.
Experience using AI-assisted development tools such as Claude Code, Gemini for developers, Cursor, or similar tools to accelerate prototyping and technical investigation.
Ability to create, evaluate, or demonstrate basic proofs of concept related to metadata systems, enrichment workflows, short-form content capabilities, internal tools, and content intelligence platforms.
Passion for storytelling, entertainment, and building the content foundations that power the future of AI-driven streaming.

Responsibilities

Define and lead the multi-year product strategy for Content Engineering & Intelligence across Paramount+ and Pluto TV.
Turn company goals into scalable investments, concentrating on metadata, content comprehension, embeddings, short-form systems, and content services.
Identify and develop new content capabilities, including multimodal enrichment, automated tagging, content graph evolution, short-form asset generation, and reusable content services for both internal and platform-facing uses.
Represent Content Engineering & Intelligence strategy at the executive and cross-company level.
Balance long-term platform investment with near-term delivery needs and measurable business impact.
Lead product strategy for content metadata architecture, modeling, and lifecycle management.
Guide product direction for feature pipelines, enrichment workflows, canonical content data systems, and internal content services.
Lead product planning for embedding generation, vector pipelines, and ML-ready content datasets.
Create short-form content engineering pipelines and develop tools and machine learning capabilities to help with content comprehension, transformation, and improvement.
Improve internal tooling and user experiences for teams that create, manage, validate, and operationalize content intelligence.
Partner with engineering and ML teams to build scalable, reliable, and cost-efficient content systems.
Align the content infrastructure with its uses, including discovery and ranking, search, personalization, experimentation, and improving the consumer experience.
Ensure platform APIs and internal workflows are designed for adoption, usability, and scale.
Lead, mentor, and grow a team of technical product managers.
Establish operating rhythms and product standards, create guidelines for the plan, and set clear prioritization frameworks across Content Engineering and Intelligence.
Foster a platform mindset focused on reuse, quality, documentation, operational excellence, and measurable business leverage.
Influence roadmaps across personalization, search, editorial, growth, content operations, design, and AI/ML teams.
Help content engineering, applied ML, and product teams operate as a unified system rather than a collection of siloed capabilities.
Define and track north-star metrics for Content Engineering & Intelligence success, including metadata completeness, quality, and freshness; pipeline reliability, latency, and operational efficiency; coverage and quality of content embeddings and enrichment; adoption and usability of content services and internal tools; and pace of onboarding new content capabilities and surfaces.
Ensure content systems are measurable, observable, and tied to downstream business impact.
Translate system health, coverage, quality signals, and workflow pain points into clear product direction.
Communicate platform impact, business outcomes, and technical tradeoffs clearly to executive stakeholders.
Stay updated on metadata systems and knowledge representation, focusing on multimodal AI and content knowledge, embeddings and vector pipelines, short workflows and internal tools, streaming infrastructure, and modernizing the media supply chain.
Bring external perspective and best practices from leading streaming, media, consumer technology, and AI-driven companies.
Help shape how Paramount Streaming builds, scales, and applies content intelligence across future AI-driven experiences.