AI Engineer (Agentic AI & Video Processing)

About Vidrush

One of the hottest companies at the intersection of AI and the Creator Economy. Vidrush is building the “lovable” way to produce videos with AI—turning a single prompt and a few assets into a polished, publish-ready edit.

How we work

• Small team, big ownership; you ship directly to users
  

• Bias to action; crisp PRs; lightweight specs; measurable outcomes
  

• Thoughtful about DX: types, tests where it counts, clean CI
  

We are seeking a highly skilled AI Engineer with deep expertise in Agentic AI, LLM deployment, and computer vision pipelines. You will be responsible for building intelligent multi-agent systems and deploying scalable AI video/image solutions on cloud-native infrastructures. This role focuses on agent orchestration, AI model deployment, and end-to-end video intelligence pipelines for our AI Video Tool.

Responsibilities

• Design and deploy LLM and CV models using AWS Batch, Fargate, Lambda, SageMaker, and Bedrock for scalable and low-latency inference.
  

• Implement multi-GPU distributed training and serverless AI inference architectures.
  

• Orchestrate multi-agent workflows using LangChain, LangGraph, AutoGen, CrewAI, OpenAI Agents SDK, and Agent OS frameworks.
  

• Develop advanced video and image processing pipelines (detection, tracking, generative AI).
  

• Build intelligent AI agent communication protocols for distributed task automation.
  

• Apply MLOps / LLMOps best practices for production-ready pipelines.
  

Qualifications

• 5+ years experience in AI/ML engineering with strong proficiency in Python.
  

• Proven track record of cloud-native AI deployments (AWS Batch/Fargate/Lambda).
  

• Expertise in Agent Orchestration frameworks (LangGraph, AutoGen, CrewAI, OpenAI Agents SDK).
  

• Strong knowledge of computer vision & generative AI (PyTorch, TensorFlow, CUDA).
  

• Experience with vectordatabases (FAISS, Milvus, Weaviate), Advanced RAG/GraphRAG, and knowledge graphs.
  

• Skilled in workflow automation, distributed inference, and AI systems architecture.
  

Nice to Have

• Multi-cloud exposure (GCP Vertex AI, Azure AI).
  

• Experience in Reinforcement Learning, context engineering, and advanced prompt design.
  

• Domain experience in fintech, healthcare, aviation, or energy.