Sr. AI Workflow Architect

Paramount•New York, NY

20d

About The Position

Paramount Streaming, a division within Paramount Global, is the home to the company's direct-to-consumer services spanning free and paid in the form of Pluto TV and Paramount+. Pluto TV is the global leader in free ad-supported TV, delivering more than 1,400 global channels and an extensive library of streaming content, including live and original channels. Paramount+, digital subscription video-on-demand and live streaming service, combines live sports, breaking news, and A Mountain of Entertainment™. Paramount+ features an expansive library of original series, hit shows and popular movies across every genre from world-renowned brands and production studios, including SHOWTIME®. The Principal AI Workflow Architect, Integration is a cross-disciplinary, hands-on technical leader focused on designing, prototyping, and delivering AI-enabled creative platform capabilities across Paramount content creation brands. This person brings deep technical judgment in animation, VFX, media systems, production technology, and creative development, and uses that judgment to architect practical AI systems that improve how creative end users work. This role partners with creative, product, research, engineering, evaluation, integration, and brand stakeholders to identify production pain points, prototype AI-assisted workflows, validate tools with real users, and support adoption across teams and divisions. They understand where AI is useful, where it introduces risk, and how to design human-centered systems that are trustworthy, repeatable, reviewable, and appropriate for production environments.

Requirements

15+ years of experience in production technology, workflow design, product development, pipeline development, creative technology, platform engineering, or related production-facing roles.
Experience building AI-powered tools, internal workflow applications, creative automation systems, media tools, or productivity tools for non-technical users.
Hands-on familiarity with AI-enabled tools, LLM-based workflows, prompt design, automation tools, agentic workflows, multimodal AI, or AI-assisted production processes.
Experience with enterprise AI platforms, LLM orchestration, RAG workflows, AI agents, multimodal AI tools, model/runtime integration, or AI evaluation practices.
Familiarity with tools such as Unreal Engine, Maya, Houdini, Nuke, Blender, ShotGrid, Ftrack, Airtable, Notion, Jira, Slack, or internal production platforms.
Ability to evaluate AI-enabled solutions from the perspective of usability, reliability, trust, risk, governance, and production readiness.
Experience with scripting, APIs, Python, JavaScript, TypeScript, no-code/low-code tools, or technical prototyping in support of workflow development.
Strong communication and collaboration skills across creative, technical, research, product, governance, and operational stakeholders.

Nice To Haves

AI systems architecture
Creative AI platform strategy
AI workflow architecture
End-user tool design
Human-centered AI integration
Production-aware systems thinking
Rapid prototyping and iteration
Workflow analysis and process improvement
Strong creative and technical judgment
Pragmatic evaluation of emerging technologies
AI evaluation, trust, governance, and auditability
Clear communication and documentation
Cross-functional collaboration
User advocacy and adoption planning
Focus on shipping tools that are genuinely usable in production

Responsibilities

Design and refine AI-integrated workflows that support creative production, production management, review, planning, documentation, asset discovery, localization, and operational handoffs.
Architect tools and workflows that incorporate large language models, multimodal AI systems, agents, retrieval workflows, automation, structured data, media-generation systems, and human-in-the-loop review.
Translate user needs, production pain points, and emerging AI capabilities into practical workflow concepts, prototypes, platform patterns, and tool requirements.
Develop repeatable AI workflow patterns that can scale across teams, departments, productions, and divisions.
Balance local runtimes, cloud AI services, enterprise platforms, vendor tools, APIs, and internal production systems as appropriate for each workflow.
Ensure AI-enabled tools are designed around clear user value, creative control, production safety, reliability, and practical adoption.
Build, configure, or guide the development of AI-powered prototypes, workflow experiments, reference implementations, and user-facing tools.
Partner with engineers, product managers, research teams, evaluation partners, and production users to test whether AI-assisted workflows are useful, controllable, repeatable, and understandable.
Create realistic use cases and pilot scenarios that reflect actual production needs, constraints, and edge cases.
Evaluate tools through hands-on testing, user feedback, workflow observation, and production-readiness criteria.
Assess usability, reliability, trust, reviewability, explainability, governance needs, and fit within existing production workflows.
Identify where AI outputs require human review, structured constraints, metadata, permissions, auditability, or additional product safeguards.
Evaluate current-state workflows, identify bottlenecks, manual effort, handoff issues, duplication, information gaps, and friction points.
Propose practical improvements that balance automation, human control, creative flexibility, speed, and production reliability.
Collaborate with brand end users and platform teams to ensure workflow designs are feasible, maintainable, secure, and aligned with platform architecture.
Help shape scalable workflow frameworks that can be adapted across Paramount brands utilizing the creative AI platform.
Contribute technical judgment to roadmap discussions, build-versus-buy decisions, model/runtime choices, and research-to-production priorities.
Act as a credible technical partner to Paramount brands adopting the creative AI platform.
Translate complex user needs into practical creative, technical, and operational experiments.
Facilitate working sessions, pilots, workflow reviews, and hands-on trials with end users to gather feedback and identify edge cases early.
Advocate for end users while balancing technical feasibility, platform strategy, governance, security, and production realities.
Create clear documentation, workflow patterns, decision notes, and adoption guidance that help teams understand and maintain AI-enabled systems.