AI Engineer (Generative AI, Agentic AI & Enterprise AI Platforms) | Dicetek UAE | Abu Dhabi, UAE

Dicetek UAE; Abu Dhabi; On-site; AED 400,000 - 700,000; Full time

Job summary

Dicetek UAE is seeking a highly experienced AI Engineer to lead the design, development, deployment, and governance of enterprise-grade AI solutions.

This role is ideal for professionals with strong backgrounds in software engineering, cloud platforms, Generative AI, Agentic AI, and Large Language Model (LLM) applications who can deliver scalable, production-ready AI solutions in complex enterprise environments.

Qualifications

• Bachelor’s degree in CS/SE/IT or related field.
• About 10 years software/architecture experience.
• Minimum 3+ years hands-on AI engineering.
• Proficiency with Generative AI and LLM-powered solutions.
• Expert-level Python programming.
• Experience with LangChain and LangGraph.
• Mandatory Semantic Kernel & AutoGen.
• Experience in RAG, embeddings, vector databases.
• Hands-on with Bedrock, Azure OpenAI, Vertex AI.
• Kubernetes, cloud-native architectures, and DevOps.

Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions.
• Build RAG architectures with embeddings, vector databases, and semantic search.
• Create multi-agent workflows using Semantic Kernel, AutoGen, LangChain, LangGraph.
• Architect scalable cloud-native microservices-based AI apps.
• Integrate LLMs into enterprise systems and apps.
• Deploy AI workloads across AWS, Azure, and hybrid clouds.
• Develop APIs and backend services with Python and FastAPI.
• Implement AI observability, governance, and guardrails.
• Support Kubernetes-based deployment, scaling, orchestration.
• Design CI/CD pipelines and DevOps automation for AI.
• Collaborate with architecture, product, and engineering teams.
• Provide technical leadership and mentorship to engineers.

Skills

Python

NumPy/Pandas

PyTorch/TensorFlow

LangChain

LangGraph

Semantic Kernel

AutoGen

RAG (embeddings)

Bedrock

Azure OpenAI

Vertex AI

APIs & Microservices

Kubernetes

DevOps & CI/CD

CI/CD Pipelines

Quality Gates

Monitoring

Education

Bachelor’s Degree in CS/SE/IT or related field

Job description

Job Title: AI Engineer (Generative AI, Agentic AI & Enterprise AI Platforms) | Dicetek UAE | Abu Dhabi, UAE

Recruiting Company:

Dicetek UAE

Job Location:

Abu Dhabi, United Arab Emirates

Job Type:

Full-Time

Additional Information

• Senior-Level AI Engineering Opportunity
• Enterprise AI & Innovation Program
• Minimum 10 Years Overall Technology Experience
• Minimum 3+ Years Hands-On AI Engineering Experience
• Experience with Generative AI and LLM-Based Solutions Required

Position Summary

Dicetek UAE is seeking a highly experienced AI Engineer to lead the design, development, deployment, and governance of enterprise-grade AI solutions. This role is ideal for professionals with strong backgrounds in software engineering, cloud platforms, Generative AI, Agentic AI, and Large Language Model (LLM) applications who can deliver scalable, production-ready AI solutions in complex enterprise environments.

Detailed Job Description

As an AI Engineer, you will be responsible for designing and implementing advanced AI-powered applications that leverage Generative AI, Agentic AI, LLMs, retrieval systems, and cloud-native architectures. You will work closely with product teams, architects, software engineers, and business stakeholders to build intelligent systems that solve real-world business challenges. The role requires hands-on expertise in AI orchestration frameworks, cloud AI platforms, vector databases, RAG architectures, Kubernetes, DevOps automation, and enterprise software engineering best practices. You will be expected to drive innovation while ensuring high standards of security, governance, scalability, observability, and operational excellence. This is a strategic opportunity to contribute to enterprise AI transformation initiatives within a rapidly evolving technology landscape.

Key Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI solutions.
• Build and optimize Retrieval-Augmented Generation (RAG) architectures using embeddings, vector databases, and semantic search technologies.
• Develop intelligent multi-agent workflows using Semantic Kernel, AutoGen, LangChain, and LangGraph.
• Architect scalable AI applications using cloud-native and microservices-based approaches.
• Integrate LLMs into enterprise systems and business applications.
• Deploy and manage AI workloads across AWS, Azure, and hybrid cloud environments.
• Develop APIs and backend services using Python and FastAPI.
• Implement AI observability, monitoring, evaluation, governance, and guardrail frameworks.
• Support Kubernetes-based deployment, scaling, and orchestration of AI solutions.
• Design and maintain CI/CD pipelines and DevOps automation for AI applications.
• Collaborate with architecture, product, and engineering teams to deliver secure and scalable AI products.
• Provide technical leadership, mentoring, and guidance to engineering teams.

Required Qualifications & Skills

• Bachelor’s Degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence, or a related discipline.
• Approximately 10 years of software engineering, cloud engineering, architecture, or platform engineering experience.
• Minimum 3+ years of hands-on AI Engineering experience.
• Strong experience delivering Generative AI and LLM-powered applications.
• Expert-level Python programming skills.
• Strong experience with NumPy, Pandas, and FastAPI.
• Hands-on experience with PyTorch and/or TensorFlow.
• Experience with LangChain and LangGraph.
• Mandatory experience with Microsoft Semantic Kernel.
• Mandatory experience with Microsoft AutoGen.
• Experience implementing RAG solutions using embeddings, semantic search, vector databases, and retrieval optimization techniques.
• Hands-on experience with Amazon Bedrock.
• Experience with Azure OpenAI Service.
• Experience with Google Vertex AI.
• Strong knowledge of APIs, microservices, event-driven architecture, and cloud-native services.
• Experience deploying AI workloads to Kubernetes environments.
• Strong DevOps, CI/CD, and automation experience.
• Experience with Jenkins and/or GitLab pipelines.
• Experience implementing release governance, quality gates, and static code analysis.
• Experience monitoring cloud, infrastructure, and AI application environments.

Nice-to-Have Skills

• AI Engineering certifications from Microsoft, AWS, or Google Cloud.
• Experience with AI governance and responsible AI frameworks.
• Knowledge of advanced AI observability platforms.
• Experience in hybrid-cloud AI deployments.
• Background in enterprise-scale digital transformation initiatives.

Key Technical Domains

• Generative AI
• Agentic AI
• Autonomous Agents
• Multi-Agent Systems
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Semantic Search
• Semantic Kernel
• AutoGen
• LangChain
• LangGraph
• Azure AI
• Amazon Bedrock
• Google Vertex AI
• Kubernetes
• Cloud-Native Architectures
• DevOps & CI/CD

Recruitment Pro Tip

For senior AI engineering roles, hiring managers prioritize candidates who can demonstrate successful production deployments of LLM-based applications. Highlight projects involving RAG implementations, multi-agent systems, Semantic Kernel, AutoGen, cloud AI platforms, vector databases, AI governance frameworks, and measurable business outcomes such as automation gains, productivity improvements, cost reductions, or customer experience enhancements.