Agentic AI Engineer - Prompt Engineering

Job Summary : We are seeking a highly skilled Agentic AI Engineer to design, develop, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs). The ideal candidate will have hands-on experience building AI agents, multi-agent systems, and RAG-based applications using modern AI orchestration frameworks. Key Responsibilities : - Design and develop AI agent workflows using frameworks such as LangGraph, LangChain, or Semantic Kernel. - Build and optimize LLM-powered applications leveraging prompt engineering, tool/function calling, and structured outputs. - Implement agentic architectures including Planner-Executor, ReAct, Multi-Agent, and Supervisor-Worker patterns. - Develop RAG solutions using vector databases and enterprise data sources. - Manage agent memory, context, state management, and workflow orchestration. - Integrate APIs, enterprise tools, and external services into AI workflows. - Build automated testing, evaluation, monitoring, and observability frameworks for AI agents. - Deploy and maintain AI solutions on AWS, Azure, or GCP environments. - Collaborate with business and technical stakeholders to translate requirements into scalable AI solutions. Required Skills : - 6-10 years of technology consulting/software development experience with 3+ years in AI/ML, GenAI, or LLM-based solutions. - Strong experience in Prompt Engineering and AI Agent development. - Hands-on expertise with LangGraph, LangChain, or Semantic Kernel. - Strong programming skills in Python (preferred) or TypeScript/JavaScript. - Experience with RAG, embeddings, vector databases (Pinecone, FAISS, Azure AI Search), and AI workflow orchestration. - Knowledge of cloud platforms (AWS, Azure, or GCP), GitHub, CI/CD, and DevOps practices. - Experience creating HLDs, LLDs, and technical solution designs. Job Summary : We are seeking a highly skilled Agentic AI Engineer to design, develop, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs). The ideal candidate will have hands-on experience building AI agents, multi-agent systems, and RAG-based applications using modern AI orchestration frameworks. Key Responsibilities : - Design and develop AI agent workflows using frameworks such as LangGraph, LangChain, or Semantic Kernel. - Build and optimize LLM-powered applications leveraging prompt engineering, tool/function calling, and structured outputs. - Implement agentic architectures including Planner-Executor, ReAct, Multi-Agent, and Supervisor-Worker patterns. - Develop RAG solutions using vector databases and enterprise data sources. - Manage agent memory, context, state management, and workflow orchestration. - Integrate APIs, enterprise tools, and external services into AI workflows. - Build automated testing, evaluation, monitoring, and observability frameworks for AI agents. - Deploy and maintain AI solutions on AWS, Azure, or GCP environments. - Collaborate with business and technical stakeholders to translate requirements into scalable AI solutions. Required Skills : - 6-10 years of technology consulting/software development experience with 3+ years in AI/ML, GenAI, or LLM-based solutions. - Strong experience in Prompt Engineering and AI Agent development. - Hands-on expertise with LangGraph, LangChain, or Semantic Kernel. - Strong programming skills in Python (preferred) or TypeScript/JavaScript. - Experience with RAG, embeddings, vector databases (Pinecone, FAISS, Azure AI Search), and AI workflow orchestration. - Knowledge of cloud platforms (AWS, Azure, or GCP), GitHub, CI/CD, and DevOps practices. - Experience creating HLDs, LLDs, and technical solution designs.