AI Engineer / Agentic AI Developer
Role overview
Job Description We are seeking experienced AI Engineers / Agentic AI Developers to design, develop, and deploy enterprise-grade AI solutions with a focus on Agentic AI , Large Language Models (LLMs) , and Retrieval-Augmented Generation (RAG) . The successful candidate will be responsible for building intelligent AI agents and workflows capable of reasoning, planning, task execution, and orchestration while ensuring all solutions are deployed in an on-premises environment using local AI models and tools. Key Responsibilities • Gather, analyze, and translate business requirements into scalable AI and Agentic AI solutions. • Design, develop, test, deploy, and maintain AI-powered applications and autonomous AI agents. • Build Agentic AI workflows capable of reasoning, planning, task execution, and orchestration. • Develop and integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures. • Integrate AI solutions with enterprise applications, APIs, databases, cloud services, and on-premises systems. • Optimize AI models, prompts, workflows, and application performance. • Ensure AI solutions comply with enterprise security, governance, privacy, and Responsible AI standards. • Prepare technical documentation, deployment guides, operational manuals, and knowledge transfer materials. • Provide technical support, troubleshooting, performance tuning, and continuous improvements. • Design and implement AI solutions using on-premises infrastructure, local models, and enterprise-approved AI tools .
Requirements • Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. • 5+ years of software development experience, including 2+ years working with AI/Generative AI technologies. • Strong experience with Python and AI application development. • Hands-on experience with Large Language Models (LLMs) and prompt engineering. • Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions. • Experience building Agentic AI or multi-agent systems. • Experience integrating AI applications with REST APIs , databases, and enterprise applications. • Familiarity with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen , or similar. • Experience working with vector databases such as Milvus, ChromaDB, FAISS, Pinecone , or equivalent. • Knowledge of model deployment using Ollama, vLLM, Hugging Face Transformers, NVIDIA NIM , or similar on-premises inference platforms. • Experience deploying and managing AI solutions in on-premises environments . • Understanding of AI security, governance, privacy, and Responsible AI principles. • Experience with Docker, Kubernetes, Git, and CI/CD pipelines is preferred. • Strong analytical, problem-solving, communication, and documentation skills. Preferred Skills • Experience with open-source LLMs such as Llama, Mistral, Qwen, Gemma, or DeepSeek . • Experience with GPU infrastructure and AI model optimization. • Knowledge of MLOps practices and AI monitoring. • Experience integrating AI solutions with enterprise platforms such as SAP, ServiceNow, Microsoft 365, or other enterprise systems. • Experience working in highly secure or regulated enterprise environments. This JD is aligned with your requirement that all AI use cases must run on-premises using local models and on-premises tools , making it suitable for enterprise or government projects.
