Senior Director, Technical Product Management, Content Engineering and Intelligence

About the role

We’ve got the brands, we’ve got the stars, we’ve got the power to achieve our mission to entertain the planet – now all we’re missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

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
• 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 include 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. 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

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. 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.
• 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

Qualifications

• 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. 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.
• 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

Skills

• 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.
• 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

• Hiring Salary Range: $203,200.00 - 304,800.00.
• The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.
• The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement.
• This position is bonus eligible.

Payscale

• Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits