VidRush is an AI-native video production platform that replaces an entire video team with coordinated AI agents.
Creators turn a simple idea into a fully produced, long-form video—research, script, voiceover, visuals, motion graphics, and rendering—in under an hour. No timelines. No editing headaches. Just intent → finished video.
We’re building a new way to create video that feels more like writing than editing, and we’re already seeing strong traction from serious creators and media teams.
If you’re excited about AI, creator tools, and building category-defining products from first principles, you’ll fit right in.
We’re hiring a Senior Python Backend Engineer (AI Agents) to help build and scale Vidrush’s AI-driven media pipeline. Vidrush is building an agentic pipeline that can turn a prompt into a full video production workflow — including script generation, voiceover, footage selection, and assembly — and we are scaling the backend team quickly to accelerate execution.
This role is fundamentally about shipping and ownership. We’re not looking for a “perfect on paper” engineer who optimizes for theoretical correctness or academic knowledge. We want someone who can take ambiguous problems, move fast, and reliably deliver tangible progress without needing to be managed.
Build agentic systems that can reason, plan, and execute multi-step tasks reliably
Design and deploy LLM-based services (tool use, structured outputs, evals, monitoring)
Develop video/image intelligence pipelines (retrieval, matching, classification, metadata extraction, generative augmentation)
Integrate existing APIs and tools when appropriate (strong build-vs-buy judgment)
Ship scalable inference pipelines on cloud infrastructure
Apply MLOps / LLMOps best practices: observability, testing, evals, versioning, cost control
Work closely with founders and product to iterate quickly based on user feedback
Strong Python engineering skills and proven ability to ship production systems
Experience building with LLMs (OpenAI-style APIs, tool calling, RAG, structured generation)
Experience deploying ML/LLM services in production (cloud, containers, serverless, async pipelines)
Practical understanding of video/image processing (CV or media pipelines)
High autonomy: you can take vague problems and turn them into shipped solutions
Strong engineering fundamentals: clean code, reliability, performance, and cost awareness
Agent orchestration frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
Experience with vector search / embeddings / retrieval systems
Experience with workflow orchestration (queues, batch jobs, event-driven systems)
Experience with PyTorch and GPU inference optimization
Experience working on media-heavy products (video editing, video generation, large file pipelines)
Small team, high trust, high ownership
Bias to action and shipping
Lightweight specs, fast iteration
Strong focus on developer experience, testing where it matters, and observability
Location preference
Turkey
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