[Remote] Senior Director, Technical Product Management, Content Engineering and Intelligence

Note: The job is a remote job and is open to candidates in USA. Paramount is on a mission to unleash the power of content, and they are seeking a Senior Director of Technical Product Management to lead the product strategy and execution for Content Engineering & Intelligence. This role involves guiding the vision for content systems, improving metadata quality, and managing workflows and services within Paramount’s global streaming ecosystem.

Responsibilities

• Define and lead the multi-year product strategy for Content Engineering & Intelligence across Paramount+ and Pluto TV
• Turn company goals into scalable investments. Concentrate on metadata, content comprehension, embeddings, short-form systems, and content services
• Identify and develop new content capabilities. These capabilities include multimodal enrichment, automated tagging, and content graph evolution. They also involve 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. Develop tools and machine learning capabilities. These tools should 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. This involves several activities. These activities involve several key areas. They include discovery and ranking. They also cover 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. 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
• Pace of onboarding new content capabilities and surfaces
• This considers how discovery and personalization are affected. It also covers short-form involvement and experimentation
• 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. Focus on multimodal AI and content knowledge. Work with embeddings and vector pipelines. Manage short workflows and internal tools. Oversee streaming infrastructure and modernize the media supply chain
• Bring external perspective and best practices from leading streaming, media, consumer technology, and AI-driven companies

Skills

• 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
• Have experience in delivering large content platforms. This includes metadata systems, internal tools, data platforms, and machine learning systems. You should have this experience 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. Knowledge of enrichment workflows and canonical metadata models. Knowledge of content identifiers, taxonomy, ontology, and content normalization methods
• Experience with data pipelines. Experience with feature stores. Experience with datasets that are ready for models. Experience with batch and near-real-time architectures. Knowledge of 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
• Experience in building or improving content intelligence capabilities. This includes personalization and recommendations. It also involves search, short-form content, content discovery, and advertising. It also involves working with 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
• You should be able to create, evaluate, or demonstrate basic proofs of concept. These proofs should be 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

Benefits

• Medical
• Dental
• Vision
• 401(k) plan
• Life insurance coverage
• Disability benefits
• Tuition assistance program
• PTO
• This position is bonus eligible
• Generous paid time off
• Opportunities for both on-site and virtual engagement events
• Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace

Company Overview

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