Principal AI Engineer​/AI Solutions Architect – GenAI & Agentic AI

Principal AI Engineer / AI Solutions Architect – GenAI & Agentic AI

Location: Abu Dhabi, UAE

Employment Type: Full-time

Workplace: On-site

Digital Next is looking for an exceptional, hands-on Principal AI Engineer / AI Solutions Architect – GenAI & Agentic AI to join our technology team in Abu Dhabi and work across major enterprise and government digital transformation programmes.

This is a senior technical role for someone who operates at the forefront of AI engineering
. We are looking for an exceptional technologist who can move from:

Complex business problem → technology research → solution architecture → rapid prototype → production deployment.

You will work across Digital Next's strategic programmes while also helping us identify and develop new AI capabilities, reusable accelerators and emerging technology solutions that differentiate Digital Next in the market.

This is not a junior AI, prompt-engineering, purely research, or management-only position
. You must be able to personally architect and build.

We are looking for someone who continuously explores the latest models, agent architectures, frameworks, development tools and engineering techniques
, understands where the AI market is moving, and can determine which technologies are genuinely ready for enterprise adoption.

You should be equally comfortable architecting complex enterprise AI solutions, writing production-quality code, rapidly building prototypes, evaluating emerging technologies, troubleshooting difficult engineering problems, and defending your technical decisions to senior stakeholders
.

• Act as a senior technical authority for AI initiatives, challenging weak architectural assumptions and recommending appropriate models, frameworks, platforms and engineering patterns.
• Own AI solutions technically from discovery and architecture through implementation, evaluation, deployment and production optimization
  .
• Architect and build advanced Generative AI and LLM applications for enterprise and government use cases.
• Design production-grade RAG architectures
  , including content ingestion, chunking, embeddings, hybrid/vector search, semantic retrieval, reranking, grounding and citations.
• Design and build AI agents and multi-agent systems that securely interact with enterprise applications, data, APIs and tools.
• Implement MCP (Model Context Protocol), tool/function calling and modern agent orchestration patterns.
• Design advanced knowledge retrieval, knowledge graph and GraphRAG solutions where appropriate.
• Evaluate and integrate frontier commercial and open-source AI models based on capability, quality, security, sovereignty, latency, scalability and cost.
• Develop production-grade Python services, APIs, AI microservices and integration components
  .
• Master modern AI-native software engineering
  , using coding agents and AI development tools to accelerate architecture exploration, implementation, testing, debugging, refactoring and documentation—while maintaining full technical ownership of generated code, security and engineering quality.
• Develop multimodal AI solutions involving documents, images, vision, speech and other modalities where appropriate.
• Design AI evaluation frameworks covering accuracy, retrieval quality, groundedness, hallucination, safety, latency, performance and cost
  .
• Implement AI security controls addressing prompt injection, indirect prompt injection, data leakage, insecure tool invocation, excessive agent permissions and other AI-specific threats
  .
• Integrate AI capabilities with enterprise platforms including CMS/DXP, DMS, search platforms, databases, APIs and business applications
  .
• Design AI solutions for cloud, private-cloud, sovereign and controlled enterprise environments
  .
• Support deployment,…