Description

Key Responsibilities

• Design and implement multi-agent AI systems and autonomous business workflows
• Develop and deploy LLM-based applications using LangChain, LlamaIndex, and Hugging Face ecosystem
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines and vector databases
• Integrate LLMs with external systems and enterprise applications via APIs
• Perform LLM fine-tuning, prompt engineering, and model performance optimization in production
• Build conversational AI interfaces, chatbots, and AI-powered applications
• Advise on best practices for AI agent development and enterprise AI integration
• Manage stakeholder communication regarding AI capabilities, limitations, and project timelines
• Produce AI system architecture and technical design documentation

Required Skills

• Python, FastAPI, Flask
• LangChain, LlamaIndex, Transformers library, PyTorch
• OpenAI API, Azure OpenAI, Anthropic Claude
• AWS Bedrock, Google Vertex AI / Google Cloud AI
• Vector databases: Pinecone, Weaviate, ChromaDB
• JavaScript / TypeScript for AI frontend integration
• Git, Docker, Kubernetes
• SQL / NoSQL databases for AI data management
• MLOps tools and practices
• API development and Postman for API testing

Preferred Skills

• Knowledge graphs and enterprise knowledge management systems
• AI agent orchestration, planning algorithms, and decision-making frameworks
• AI safety practices and responsible AI principles
• Experience with at least three complete end-to-end agentic AI system implementations

Key Skills

Education

Bachelor's degree