EMSTEEL — one of the UAE’s leading steel and building-materials groups — is seeking a highly skilled Sr. Digital Delivery Specialist for its Digital Centre of Excellence in Abu Dhabi. You will design, build, and deliver advanced AI and machine-learning solutions that create measurable business value across EMSTEEL’s steel and building-materials operations — covering Generative AI, Agentic AI, Computer Vision, AI Digital Twins, and production-grade MLOps applied to industrial use cases including process optimization, predictive maintenance, quality prediction, energy optimization, and anomaly detection in a real manufacturing environment.
About EMSTEEL — Digital Centre of Excellence Abu Dhabi
Organisation: EMSTEEL — a leading UAE steel and building-materials group operating the Digital Centre of Excellence, driving AI and ML transformation across its industrial operations
AI Scope: Generative AI (LLM-based assistants, RAG pipelines, document intelligence), Agentic AI (autonomous multi-agent systems, A2A collaboration), Computer Vision, AI Digital Twins, industrial ML models
Platform Stack: Databricks (Spark, Delta Lake, Unity Catalog), Microsoft Azure stack (Azure Machine Learning, Azure OpenAI, Azure AI Foundry, Fabric/Synapse), Dataiku
MLOps: MLflow, Docker/Kubernetes, CI/CD via GitHub Actions, model registry, versioning, monitoring, drift detection, and automated retraining pipelines
Industrial Domains: Process optimization, predictive maintenance, quality prediction, energy and yield optimization, defect detection, and safety monitoring on the steel shop floor
Industrial AI in Abu Dhabi — Why EMSTEEL & Why Now
Strategic Context: EMSTEEL’s Digital Centre of Excellence is at the frontier of industrial AI adoption in the UAE — applying Generative AI, Agentic AI, and Computer Vision to steel manufacturing operations where AI-driven improvements in process efficiency, yield, quality, and energy use have direct, measurable commercial impact
Market Rarity: Senior AI engineers who combine GenAI/LLM delivery experience, Agentic AI systems capability, MLOps production engineering, and genuine industrial/manufacturing domain exposure are among the most sought-after and premium-compensated technology professionals in the UAE
Technology Frontier: EMSTEEL’s use of Databricks, Azure AI Foundry, Azure OpenAI, Dataiku, and cutting-edge agentic frameworks places this role at the leading edge of enterprise AI engineering in the GCC industrial sector
Career Growth: Clear progression toward Lead AI Engineer, AI Architect, and Head of Digital Delivery roles within EMSTEEL’s expanding Digital Centre of Excellence
Position Overview
This Sr. Digital Delivery Specialist role at EMSTEEL in Abu Dhabi covers the full end-to-end AI and ML delivery lifecycle — from use-case discovery and stakeholder qualification, through design and development of Generative AI solutions (LLM-based assistants, RAG pipelines, document intelligence), building Agentic AI systems with autonomous multi-agent workflows, delivering industrial AI use cases (process optimization, predictive maintenance, quality prediction, anomaly detection), developing AI Digital Twins and Computer Vision solutions, implementing MLOps practices (CI/CD, model registry, monitoring, drift detection), engineering scalable pipelines on Databricks and Azure, driving adoption through change management, and establishing responsible AI governance — all within EMSTEEL’s industrial steel and building-materials operating environment.
Why This Role Matters: As Sr. Digital Delivery Specialist at EMSTEEL’s Digital Centre of Excellence in Abu Dhabi, you are building the AI and ML systems that transform how a major UAE steel and building-materials group operates — where a well-designed predictive maintenance model prevents unplanned equipment shutdowns, a quality prediction algorithm reduces defect rates and rework costs, a Computer Vision system catches surface defects the human eye misses, and a GenAI assistant helps engineers access operational knowledge that was previously siloed in documents and experienced heads, apply the rare combination of Generative AI delivery experience (LLMs, RAG, embeddings, prompt engineering, vector databases), Agentic AI systems capability (autonomous multi-agent workflows, A2A collaboration using LangChain, LangGraph, Semantic Kernel, or AutoGen), and industrial AI domain expertise (process optimization, predictive maintenance, AI digital twins) in a single role where all three disciplines are simultaneously active and genuinely valued, operate across the full AI engineering stack — Python data science and ML modelling, deep learning and Computer Vision, MLOps with MLflow and Docker/Kubernetes on Databricks, Azure AI Foundry and Azure Machine Learning, and Dataiku — in a production manufacturing environment where model reliability, monitoring, and responsible AI governance are not aspirational goals but operational requirements, contribute to EMSTEEL’s AI reference architecture, reusable components, and internal best-practice standards — building the organisational AI capability that persists and compounds beyond any individual project, and build a senior industrial AI engineering career at one of the UAE’s most technically ambitious manufacturing groups — where your contributions to process efficiency, quality, safety, and energy optimization have measurable impact on EMSTEEL’s commercial performance and competitive position.
Key Responsibilities
Generative AI & Agentic AI Delivery
- Design, develop, and deploy Generative AI solutions — LLM-based assistants, RAG pipelines, document intelligence, summarisation, and content generation — tailored to EMSTEEL’s enterprise and industrial needs
- Build Agentic AI systems — autonomous and multi-agent workflows that reason, plan, use tools, and orchestrate tasks — including Agent-to-Agent (A2A) collaboration across enterprise applications using LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent frameworks
- Apply expertise in prompt engineering, embeddings, vector databases, fine-tuning, and LLM evaluation — ensuring GenAI solutions meet accuracy, safety, bias, and cost-control requirements
- Establish responsible AI governance and guardrail practices for GenAI and agentic solutions — covering data privacy, evaluation frameworks, and production safety controls
Industrial AI — Process Optimization, Predictive Maintenance & Digital Twins
- Deliver industrial AI use cases across EMSTEEL’s steel and building-materials value chain — process optimization, predictive maintenance, quality prediction, energy and yield optimization, and anomaly detection
- Develop and operationalize AI Digital Twin solutions that simulate, monitor, and optimize plant assets and production processes in real time
- Develop, validate, and optimize classical and deep-learning models for prediction, optimization, anomaly detection, and process control across EMSTEEL’s industrial operations
- Partner with business stakeholders and subject-matter experts to identify, qualify, and prioritize high-impact AI/ML use cases aligned to EMSTEEL’s strategic objectives
Computer Vision & MLOps Engineering
- Build Computer Vision solutions for defect detection, surface-quality inspection, safety monitoring, and process automation on the steel shop floor — using OpenCV, PyTorch/TensorFlow, object detection, and segmentation
- Implement robust MLOps practices — CI/CD for models, automated pipelines, feature stores, model registry, versioning, monitoring, drift detection, and retraining — using MLflow, Docker/Kubernetes, and GitHub Actions
- Engineer scalable data and AI pipelines on Databricks (Spark, Delta Lake, Unity Catalog) — integrating solutions across the Microsoft Azure stack (Azure ML, Azure OpenAI, Azure AI Foundry, Fabric/Synapse) and Dataiku
- Own end-to-end AI project delivery from proof-of-concept through to production — ensuring quality, security, performance, and on-time delivery across the full project lifecycle
Adoption, Architecture & Continuous Learning
- Drive AI adoption by embedding solutions in downstream applications, updating SOPs, enabling end users, and delivering relevant training and change management across EMSTEEL’s operations
- Contribute to EMSTEEL’s AI reference architecture, reusable components, and internal best-practice standards within the Digital Centre of Excellence
- Stay current with emerging GenAI/agentic frameworks, foundation models, and tooling — piloting promising innovations that could accelerate EMSTEEL’s industrial AI programme
- Mentor junior Digital Delivery Specialists and analysts — supporting a culture of experimentation, continuous learning, and responsible AI practice across the team
Qualifications & Requirements
Educational Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering, Physics, or Mathematics (REQUIRED)
- Certifications in Machine Learning/AI, Databricks, Microsoft Azure AI, or Dataiku are an advantage
Experience Requirements
- 4+ years in data science / machine learning delivery (REQUIRED)
- Demonstrated delivery of GenAI or Agentic AI solutions to production (REQUIRED)
- 2+ years implementing cutting-edge AI/GenAI technologies (REQUIRED)
- 1+ years of work experience with Agentic AI development (REQUIRED)
- 2+ years implementing MLOps practices in production environments (REQUIRED)
- Exposure to manufacturing, heavy industry, or steel operations is a strong advantage
- Experience with responsible AI governance and LLMOps frameworks
Technical Skills
- Strong hands-on Python (and SQL) for machine learning, deep learning, and statistical modelling
- Proven expertise in Generative AI — LLMs, prompt engineering, RAG, embeddings, vector databases, and fine-tuning
- Experience building Agentic AI and multi-agent/A2A systems using LangChain, LangGraph, Semantic Kernel, AutoGen, or similar
- Hands-on Computer Vision experience — OpenCV, PyTorch/TensorFlow, object detection, segmentation, defect and anomaly detection
- Solid MLOps capability — MLflow, Docker/Kubernetes, CI/CD, GitHub Actions, model monitoring, and drift detection
- Proficiency with Databricks (Spark, Delta Lake, Unity Catalog) and working knowledge of Microsoft/Azure AI stack and Dataiku
About EMSTEEL — Digital Centre of Excellence
EMSTEEL is one of the UAE’s leading steel and building-materials groups — and its Digital Centre of Excellence represents the company’s commitment to becoming a truly AI-native industrial organisation. By applying Generative AI, Agentic AI, Computer Vision, AI Digital Twins, and rigorous MLOps practices to steel manufacturing operations, EMSTEEL is building the kind of AI-driven operational capability that creates durable competitive advantage — smarter process control, lower defect rates, more effective predictive maintenance, and better energy efficiency across the production value chain. For a senior AI engineer who combines technical depth across the full modern AI stack with the ambition to apply it in a genuinely consequential industrial context, EMSTEEL’s Digital Centre of Excellence in Abu Dhabi is one of the most technically exciting and professionally rewarding roles in the UAE’s AI engineering market in 2026.
Career Excellence: Join EMSTEEL’s Digital Centre of Excellence as Sr. Digital Delivery Specialist in Abu Dhabi — where Generative AI, Agentic AI, Computer Vision, industrial Digital Twins, production-grade MLOps, and Databricks/Azure engineering combine in one of the UAE’s most ambitious and technically sophisticated industrial AI transformation programmes.
Who Should Apply?
- Senior GenAI/LLM Engineers: With 2+ years of Generative AI production delivery experience — RAG pipelines, LLM-based assistants, document intelligence, embeddings, and vector databases
- Agentic AI Systems Engineers: With 1+ years of Agentic AI development experience — autonomous multi-agent systems, A2A collaboration, LangChain, LangGraph, Semantic Kernel, or AutoGen
- Industrial AI / MLOps Engineers: With 2+ years of MLOps production engineering and exposure to manufacturing, heavy industry, or process optimization AI use cases
- Computer Vision Engineers: With defect detection, surface inspection, and safety monitoring CV model development experience using PyTorch/TensorFlow on manufacturing shop floor applications
- Databricks & Azure AI Engineers: With Spark, Delta Lake, Azure ML, Azure OpenAI, and AI Foundry experience — building scalable data and AI pipelines in enterprise industrial environments
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