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.

VidRush

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AI Engineer (Agentic AI & Video Processing)