AI Engineer (Agentic AI & Video Processing)

Posted 8 days ago

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

Apply now

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.