AI Engineer / Agentic AI Developer

Müller`s Solutions; United Arab Emirates; On-site; AED 180,000 - 280,000; Full time

Job summary

Müller’s Solutions seeks experienced AI Engineers to design, develop, and deploy enterprise-grade AI solutions with a focus on Agentic AI, LLMs, and RAG. You will build intelligent agents capable of reasoning, planning, and execution, deployed on-premises with local models and tools.

The role requires 5+ years of software development, 2+ years in AI technologies, strong Python skills, and experience implementing on-prem AI platforms.

Qualifications

• Bachelor's degree in CS/AI or related field.
• 5+ years software development with 2+ years in AI tech.
• Strong Python and AI application development experience.
• Experience with on-premises AI deployments and security.

Responsibilities

• Gather, analyze, and translate business requirements into scalable AI solutions.
• Design, develop, test, deploy, and maintain AI-powered applications and agents.
• Build agentic AI workflows with reasoning, planning, and execution capabilities.
• Integrate LLMs, RAG, and multi-agent architectures into enterprise systems.
• Ensure on-premises deployment with local models and approved tools.
• Document deployment guides and provide knowledge transfer.
• Provide troubleshooting, performance tuning, and continuous improvements.

Skills

Python

AI development

Problem solving

Communication

Education

Bachelor's degree in Computer Science / AI / Software Engineering

Tools

Docker

Kubernetes

Git

CI/CD pipelines

LangChain / LangGraph

LlamaIndex

CrewAI

AutoGen

Milvus

ChromaDB

FAISS

Pinecone

Ollama

vLLM

Hugging Face Transformers

NVIDIA NIM

Job description

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 .

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.