Toogeza
AI Video Agent Engineer
1mo ago
Worldwideaivideo editingmulti-agent systemspipeline orchestration
Engineer role to design and implement multi-agent AI pipelines for video production system.
Nice to have
- The following qualifications are not mandatory, but will significantly strengthen a candidate’s profile during the evaluation process:
Other
- We are toogeza , a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for AI Video Agent Engineer for Elva .
- Location: Remote Job Type: Full-Time
- We are building an AI-driven video production system designed as an intelligent multi-agent orchestration layer capable of transforming raw ideas and references into fully structured video content.
- The system operates as a black-box creative engine for different types of users:
- professional video creators
- casual users
- creators of short narrative concepts
- Users provide an idea, references, or media fragments , and the system automatically orchestrates multiple AI agents responsible for analysis, scripting, editing, and production of video content .
- We are looking for an engineer who can design and implement multi-agent pipelines , orchestrate AI tools, and build intelligent workflows that combine video analysis, storytelling logic, and automated editing .
- This role sits at the intersection of AI systems architecture, creative tooling, and multimodal content generation .
- Design and implement the architecture of a multi-agent video editing system including agents responsible for:
- video analysis
- narrative generation
- editing orchestration
- production and output synthesis
- Define system prompts, behavioral rules, and structured instructions for agents interacting within the pipeline.
- Develop and maintain complex orchestration pipelines in n8n , including:
- multi-agent workflows
- tool-calling logic
- dynamic routing between tools and models
- context passing between agents
- Pipelines must be capable of selecting the most appropriate models, tools, and strategies depending on the task.
- Design robust pipelines for handling:
- video materials
- image assets
- user text prompts
- structured metadata
- Ensure proper data transformation and context transfer across the pipeline stages.
- Integrate both external and internal APIs for multimodal generation and processing, including:
- image generation
- video generation
- speech synthesis
- audio generation
- video processing services
- Rapidly evaluate available APIs and select the best quality tools and models for each task.
- Tune and optimize model interactions, primarily based on Gemini models , including:
- prompt engineering
- structured outputs
- tool-calling workflows
- agent collaboration logic
- Optimize pipelines for quality, reliability, and execution efficiency .
- Design systems that support:
- vector databases
- retrieval-augmented generation (RAG)
- memory and contextual reasoning between agents
- The pipeline system should be capable of:
- Taking an idea + references as input
- Analyzing the content
- Generating a coherent narrative structure
- Selecting appropriate visual and audio elements
- Producing a high-quality, structured video output
- Strong experience building multi-agent systems , including:
- intent and sub-intent modeling
- agent orchestration
- agent communication and transport layers
- summarization pipelines
- context passing between agents
- Hands-on experience with:
- n8n
- Agent tool-calling