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# Python Backend Engineer (AI / Agents

- **Company:** Vidrush Ai Studios Llp
- **Location:** UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Automated Storage and Retrieval Systems, Cloud Computing, Python (Programming Language), Search Technologies, Management of Software Versions, Video Editing, Workflow Management Systems, Pytorch, Large Language Models, Multi-Agent Systems, Event Driven Architecture, Machine Learning Operations, Serverless Computing
- **Published:** September 5, 2026
- **Apply:** https://startup.jobs/senior-python-backend-engineer-ai-agents-vidrush-ai-studios-llp-8340827

## About the Role

* 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

Nice to Have

 * 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)

How We Work

 * 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

## Description

* 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


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