AI Video Agent Engineer
Toogeza
| Company | Toogeza |
| Category | Engineering |
| Location | Europe |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 2 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
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
OVERVIEW:
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.
RESPONSIBILITIES:
AI Agent Architecture
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.
Pipeline Orchestration (n8n)
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.
Multimodal Data Processing
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.
Tool & API Integration
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.
Model Orchestration & Optimization
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.
Future Architecture (RAG & Knowledge Systems)
Design systems that support:
- vector databases
- retrieval-augmented generation (RAG)
- memory and contextual reasoning between agents
EXPECTED OUTCOMES:
The pipeline system should be capable of:
1. Taking an idea + references as input
2. Analyzing the content
3. Generating a coherent narrative structure
4. Selecting appropriate visual and audio elements
5. Producing a high-quality, structured video output
REQUIREMENTS:
AI Systems & Agent Architecture
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
Workflow Orchestration
Hands-on experience with:
- n8n
- Agent tool-calling
- n8n MCP
Experience designing complex automation pipelines is essential.
Programming
Strong practical coding skills with vibe coding mindset:
Primary languages:
- Python
- JavaScript
Bonus experience:
- ComfyUI custom nodes
- lightweight APIs (e.g., HuggingFace Spaces or inference endpoints)
Multimodal Tooling Knowledge
Ability to quickly navigat
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