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data delivery manager – data science & ai focus Jobs in Abu Dhabi With Doh Jobs In Abu Dhabi United Arab Emirates

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data scientist ai ml

Khazna Data Centers

<div>
 
 
 Khazna was founded in 2012 and has grown rapidly into becoming the leading and trusted wholesale Data Center provider in the Middle East and North Africa region. Through our Data Centers, we provide industry benchmark levels of power supply and cooling services to better serve the growing need for data center operations in the UAE and wider region.
 
 
 
 
 
 
 We are seeking a
 
 Data Scientist (AI/ML)
 
 to join our
 
 Command &amp; Control Center &ndash; Data Analytics &amp; Reporting
 
 team, reporting to the
 
 Manager, Data &amp; BI
 
 . This centralized role is responsible for developing AI-driven solutions, machine learning models, and advanced analytics to enhance data center operations, efficiency, and innovation. The Data Scientist will apply predictive modeling, deep learning, and other data science techniques to enable data-driven decision-making and automation across the data center ecosystem.
 
 
 
 
 
 
 Key Accountabilities:
 
 
 
 
 
 <ul>
 <li>
 In collaboration with the line manager, develop Data Center AI/ML models for predictive maintenance, anomaly detection and capacity planning, reducing downtime and optimizing resource allocation
 </li>
 <li>
 Support in simulation models to assess potential business impact, forecasting power demand, cooling efficiency and IT workload fluctuations
 </li>
 <li>
 Work with big data technologies and cloud platforms, optimizing AI model deployment across hybrid and multi-cloud architectures
 </li>
 <li>
 Optimize Data Center models for performance, scalability and interpretability, ensuring they align with real-time decision-making needs of mission-critical facilities
 </li>
 <li>
 Conduct statistical analysis and hypothesis testing, providing data-driven insights for risk assessment, asset lifecycle management and energy efficiency improvements
 </li>
 <li>
 Collaborate with Data Engineers to ensure seamless data pipeline integration, enabling real-time AI-driven monitoring and automation
 </li>
 <li>
 Support in develop anomaly detection algorithms to proactively identify deviations in data center power usage effectiveness (PUE), cooling efficiency etc.
 </li>
 <li>
 Research and implement emerging AI/ML technologies within data center, such as federated learning, reinforcement learning and generative AI, to enhance operational resilience
 </li>
 <li>
 Evaluate and improve the performance of existing AI models within data center, incorporating adaptive learning techniques to refine predictions over time
 </li>
 <li>
 Ensure AI/ML models in data center are continuously updated with live data streams, adapting to infrastructure expansions, workload shifts and market trends
 </li>
 <li>
 Extract findings from AI-driven analysis and present actionable insights to executives at Khazna and CCC leadership to inform strategic decision-making
 </li>
 <li>
 Support in defining and prioritize potential data center operational scenarios, using AI simulations to model the likelihood and impact of various facility and market dynamics
 </li>
 <li>
 Update data center models and forecasts based on real-time data, industry benchmarks and shifting internal prioritises to maintain competitive intelligence
 </li>
 <li>
 Drive automation in incident response and capacity forecasting, integrating AI insights with CAFM and orchestration tools for proactive management
 </li>
 <li>
 Ensure AI governance, model explainability and compliance with regulatory standards in data center operations, including SOC 2, ISO 27001 and Uptime Institute guidelines as recommended
 </li>
 </ul>
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s or Bachelor&rsquo;s in Computer Science, AI/ML (or) Data Science
 </li>
 <li>
 Certifications in AI/ML or data science preferred (e.g., Google AI, Microsoft AI)
 </li>
 <li>
 3-5 years of experience in AI/ML model development, data science or analytics
 </li>
 <li>
 Proficiency in Python, TensorFlow or PyTorch
 </li>
 <li>
 Hands-on experience with cloud-based ML platforms (AWS SageMaker, Azure ML, Google AI)
 </li>
 <li>
 Strong background in statistical modeling, probability and data structures
 </li>
 <li>
 Experience with big data frameworks like Apache Spark or Hadoop
 </li>
 </ul>
 
 
 
 
 
 Additional Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Ability to translate complex data into actionable insights for business and operational teams
 </li>
 <li>
 Expertise in explaining AI/ML concepts to non-technical leadership, ensuring alignment between data science and business strategy
 </li>
 <li>
 Work effectively across Engineering and Operations, adapting models to shifting business priorities and technological advancements
 </li>
 </ul>
 
 
 
 
 
 Trainings/Certifications Preferred:
 
 
 
 
 
 <ul>
 <li>
 Google TensorFlow Developer Certification
 </li>
 <li>
 AWS Certified Machine Learning &ndash; Specialty
 </li>
 <li>
 Microsoft Certified: Azure AI Engineer Associate
 </li>
 </ul>
 
 
</div>

Data Scientist (AI/ML)

Presight AI Ltd.

A leading AI data analytics firm is seeking a qualified Data Scientist to develop AI-powered solutions for public safety. The role focuses on LLMs and conversational AI frameworks. Responsibilities include building autonomous AI solutions and collaborating with data scientists and engineers. Candidates should have a degree in a relevant field, along with practical experience in AI and strong programming skills, particularly in Python.

AI Data Scientist - Agentic LLMs for Public Safety

Yokogawa

<div><div>Not just a job, but a career</div><div>
Yokogawa, award winner for &lsquo;Best Asset Monitoring Technology&rsquo; and &lsquo;Best Digital Twin Technology&rsquo; at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.</div><div></div><div>
Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect.</div><div></div><div>
About the Team 
Our 18,000 employees work in over 60 countries with one corporate mission, to &quot;co-innovate tomorrow&quot;. We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do.</div><div></div><div>
Job Purpose</div><ul><li>
In this role, you will drive the design, development, and implementation of advanced AI/ML models, working closely with cross-functional teams to optimize operations and deliver data-driven insights in challenging industrial environments.</li><li>
Design and develop AI /ML models that support asset performance management across various maintenance strategies, including predictive, prescriptive, and cognitive maintenance.</li><li>
Implement Analytical AI techniques (supervised/unsupervised learning, reinforcement learning) for predictive maintenance, defect elimination, and asset strategy optimization</li><li>
Use AI /ML to analyze trends and patterns, make intelligent recommendations, and automate decision support systems.</li><li>
Develop intelligent recommendations systems that improve maintenance processes, criticality assessments, and reliability analytics.</li><li>
Ensure AI models are scalable and deployable within industrial platforms, integrating with DCS, PLC, SCADA, Historians, EAM, MES/MOM, SCM, and SAP systems.</li><li>
To oversee the expansion of our advanced automation and digital transformation solutions (AI/ML) and services into new asset developments and brownfield optimization projects across several industrial markets</li></ul><div></div><div>
Key Responsibilities &amp; Accountabilities</div><ul><li>
Knowledge of software development process and technical skills: Lead AI /ML Engineer must know the technical aspects of projects to identify risks, propose immediate solutions and provide guidance for Digital transformation solutions.</li><li>
Define the AI/ML strategy and roadmap for oil &amp; gas solutions, aligning with Yokogawa&rsquo;s digital transformation objectives.</li><li>
Architect end-to-end ML systems, from data ingestion and feature engineering to model deployment and monitoring.</li><li>
The objective is to understand your customer&rsquo;s business objectives to align with Yokogawa capabilities and solutions. In this role you will lead other Yokogawa key contributors in an overall strategy to implement solutions that will contribute to customer business objectives in a way that is meaningful and measurable in the areas of AI/ML solutions.</li><li>
Lead and mentor a multidisciplinary team of data scientists, machine learning engineers, and software developers.</li><li>
Make strategy, implement initiatives &amp; measures to help position AI/ML solutions to achieve long term sustainability and profitability on establishing site services orders, management of warranty &amp; post-delivery support for YUAE business.</li><li>
Report to Department Manager-Advanced Solutions Department on job progress, issues and resolutions and manpower-mapping for effective delivery of solution.</li><li>
Lead and mentor a multidisciplinary team of data scientists, machine learning engineers, and software developers.</li></ul><div></div><div><div>
Qualification and Experience</div></div><ul><li>
A bachelor&rsquo;s degree in data science / AI or Software engineering with specialization in data science and having strong process knowledge. Master&rsquo;s degree is preferable.</li><li>
Minimum 15 years of experience.</li></ul><div></div><div>
Competencies</div><ul><li>
Develop and optimize algorithms for real-time analytics and predictive maintenance in upstream, midstream, and downstream operations.</li><li>
Perform model performance tuning to ensure reliability and scalability under production environments.</li><li>
Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions.</li><li>
Ensure all AI/ML solutions comply with industry regulations, safety standards, and data governance policies.</li><li>
Proactively addresses potential risks related to data privacy, model bias, and operational safety.</li><li>
Capable of managing field surveys, designing automation functions, and ensuring compliance with project quality standards.</li><li>
Capable of overseeing multiple projects, ensuring the successful delivery of projects involving advanced automation technologies including AI/ML and managing all aspects of project execution</li><li>
Deep technical knowledge in process solutions and expertise in specialty Chemicals &amp; Process, including understanding Chemical Properties, Manufacturing Processes, Operations and Industry-specific challenges</li><li>
Stay updated on the latest trends, technologies, and regulations in the specialty chemicals &amp; Process industry and provide insights that influence product/service/solution development and strategic planning</li><li>
Customer Focus with Strategic Mindset</li><li>
Proven track record of field experience and technical skills</li><li>
Excellent verbal and written communication skills</li><li>
Good leadership skills</li></ul><div></div><div>
Skills</div><ul><li>
Knowledge and experience in implementing AI /ML Project</li><li>
Knowledge in advanced level for programing in Python, C++, Java, C#, SQL, Matlab etc</li><li>
Strong experience with Predictive Analytics and Prescriptive Analytics using tools like TensorFlow, PyTorch, and familiarity Keras, XGBoost.</li><li>
Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.</li><li>
Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.</li><li>
Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making.</li><li>
Hands-on experience with major cloud platforms (AWS, Azure, or GCP) for model deployment and data processing.</li><li>
Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.</li><li>
Familiarity with distributed data processing and big data technologies (Spark, Hadoop), plus knowledge of time-series databases (e.g., InfluxDB, OSIsoft PI) is an added advantage.</li><li>
Knowledge of working on DCS platforms.</li><li>
Consistently demonstrates exceptional technical skills, competence, and productivity.</li><li>
Possesses excellent communication and interpersonal abilities.</li><li>
This position is best filled by someone with a firm understanding and knowledge in AI /ML with data science background with having process Plant Operations -Onshore /Offshore/Refining -Upstream, Midstream &amp; downstream with Process Automation/Process Control in both discrete and continuous manufacturing.</li></ul><div></div><div>
Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.</div><div></div><div>
Are you being referred to one of our roles? If so, ask your connection at Yokogawa 
about our Employee Referral process!</div></div>

Solutions Manager -AI & ML -Digitalization Project

Deeplight

<div>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
The AI Platform Engineer helps design, build and maintain the on-premises AI Infrastructure for our client, a market leader in the environment sector. The engineer plays a key role in enabling large-scale machine learning and generative AI workloads by developing robust, scalable, and secure platform solutions that support data scientists and ML engineers across the organisation.
The role requires deep Kubernetes and infrastructure automation experience to optimise performance, streamline deployments, and ensure reliability in an on-prem environment.
Requirements<ul>
<li>
Design, deploy, and manage on-premises Kubernetes clusters for AI and ML workloads.</li>
<li>Develop and maintain infrastructure-as-code using tools like Terraform, Helm, or Ansible</li>
<li>Build and optimise AI/ML pipelines and MLOps workflows for model training, deployment, and monitoring.</li>
<li>Collaborate with data science and engineering teams to deliver high-performance computing environments for large model training and inference.</li>
<li>Implement resource management, observability, and scaling strategies for GPU-based workloads.</li>
<li>Manage containerisation, networking, and storage solutions for AI workloads.</li>
<li>Ensure security, compliance, and reliability of the AI platform.</li>
<li>Automate operational processes and continuously improve platform efficiency.</li>
</ul>
What we need from you:<ul>
<li>
Proven experience managing Kubernetes clusters on-premises (not just cloud-managed solutions).</li>
<li>Experience working in a Consultancy capacity.</li>
<li>Strong background in container orchestration, CI/CD, and automation.</li>
<li>Proficiency in Linux administration, Docker, and networking fundamentals.</li>
<li>Hands-on experience with infrastructure-as-code (Terraform, Helm, Ansible, etc.).</li>
<li>Experience supporting AI/ML workloads (e.g., TensorFlow, PyTorch, Hugging Face, Ray, Kubeflow).</li>
<li>Familiarity with GPU scheduling and resource management on Kubernetes.</li>
<li>Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK, etc.).</li>
<li>Strong scripting skills (Python, Bash, or Go).</li>
<li>Understanding of DevOps and MLOps best practices.</li>
</ul>
Benefits
Benefits &amp; Growth Opportunities:<ul><li>Competitive salary and performance bonuses</li><li>Comprehensive health insurance</li><li>Professional development and certification support</li><li>Opportunity to work on cutting-edge AI projects</li><li>International exposure and travel opportunities</li><li>Flexible working arrangements</li><li>Career advancement opportunities in a rapidly growing AI company</li></ul>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.</div>

AI Platform Engineer

Hays

<div>
 
 
 Location:
 
 Abu Dhabi, United Arab Emirates
 
 
 
 Industry:
 
 Quantitative Research
 
 
 
 
 
 We are looking for a highly motivated and experienced
 
 Lead Data Scientist
 
 to head our data science team in Abu Dhabi.
 
 
 
 
 
 
 About the Role:
 
 
 
 As Lead Data Scientist, you will be responsible for defining and implementing advanced data science solutions, leading a team of 10 professionals. This role requires strong technical expertise, strategic leadership, and hands-on involvement in developing machine learning architectures and models.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Provide technical leadership to a team of data scientists and machine learning engineers.
 </li>
 <li>
 Design and implement data solutions for applications in BFSI, quantitative research, and asset management.
 </li>
 <li>
 Develop and optimize ML models, including LLMs and NLP pipelines, in multi-GPU environments.
 </li>
 <li>
 Define scalable and robust architectures for data processing and predictive modeling.
 </li>
 <li>
 Act as the team&rsquo;s technical reference, promoting best practices and continuous innovation.
 </li>
 <li>
 Communicate technical insights clearly to both technical and non-technical stakeholders.
 </li>
 <li>
 Collaborate with cross-functional teams to integrate data capabilities into products and workflows.
 </li>
 </ul>
 
 
 
 
 
 What We&rsquo;re Looking For:
 
 
 <ul>
 <li>
 7+ years of experience in applied data science within BFSI, quantitative research, or asset management.
 </li>
 <li>
 Proven experience in technical leadership and team management.
 </li>
 <li>
 Strong expertise in Machine Learning, LLMs, NLP, and foundational models.
 </li>
 <li>
 Hands-on experience with Python, TensorFlow, PyTorch, Scikit-learn, among others.
 </li>
 <li>
 Ability to work hands-on in complex technical environments.
 </li>
 <li>
 Excellent communication skills in English (written and verbal).
 </li>
 </ul>
 
 
 
 
 
 Academic Background:
 
 
 <ul>
 <li>
 Master&rsquo;s or PhD in relevant fields, preferably from top-tier universities (Ivy League, Oxbridge, ETH, etc.)
 </li>
 </ul>
 
 
 
 
 
 What We Offer:
 
 
 <ul>
 <li>
 Competitive, tax-free salary.
 </li>
 <li>
 Visa sponsorship (if needed).
 </li>
 <li>
 Health insurance for you and your family.
 </li>
 <li>
 Annual return ticket to your home country.
 </li>
 </ul>
 
 
</div>

Lead Data Scientist

CloudJune Technologies LLC

Job SummaryAs a Senior Data Engineer, you will be a foundational architect, responsible for designing, building, and maintaining the robust, scalable, secure, and high-performance data infrastructure that powers our AI/ML initiatives. You will work closely with Data Scientists, AI Engineers, AIOps/MLOps Engineers, and Software Engineers to ensure the seamless flow of data from diverse government sources into our AI/ML pipelines, enabling the development and deployment of impactful intelligent applications across Abu Dhabi.What You'll Do:&#9679; Design, build, and maintain scalable and reliable data pipelines for ingesting, transforming, and storing large and complex datasets from various government sources (structured, semi-structured, and unstructured).&#9679; Architect and implement data warehousing and data lake solutions on cloud platforms (primarily Azure) to provide a centralized and accessible data foundation for AI/ML and analytics.&#9679; Develop and optimize ETL/ELT processes using industry-standard tools and technologies (e.g., Azure Data Factory, Databricks, Kafka) to ensure data quality, integrity, and efficient processing.&#9679; Implement and manage data governance policies and procedures, ensuring data security, compliance with government regulations, and adherence to data quality standards.&#9679; Collaborate with Data Scientists and AI Engineers to understand their data requirements and build data pipelines that meet their specific needs for model development and evaluation.&#9679; Work closely with AIOps/MLOps Engineers to ensure seamless integration of data pipelines with AI/ML workflows and deployment processes.&#9679; Design and implement data monitoring and alerting systems to proactively identify and resolve data quality issues and pipeline failures.&#9679; Optimize data storage and retrieval systems for performance and cost-efficiency, leveraging appropriate database technologies (relational, NoSQL, vector, graph).&#9679; Implement data security measures including access control, encryption, and data masking to protect sensitive government data.&#9679; Develop and maintain data catalogs and data lineage solutions to ensure data discoverability, understand data flow, and facilitate data governance.&#9679; Evaluate and adopt new data engineering tools and technologies to continuously improve our data infrastructure and processes.&#9679; Troubleshoot and resolve data-related issues across the data lifecycle, ensuring data availability and reliability for AI/ML and analytics.&#9679; Document data pipelines, data models, and data engineering processes clearly and concisely for both technical and non-technical stakeholders.What You'll Bring:&#9679; Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field with a strong focus on data management and infrastructure.&#9679; At least 3 years of hands-on experience in designing, building, and maintaining data pipelines and data infrastructure in a production environment.&#9679; Deep understanding of data warehousing concepts, data modeling techniques (e.g., Kimball, Inmon), and data lake architectures.&#9679; Proven experience with cloud platforms, especially Microsoft Azure, and their data engineering services (e.g., Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks).&#9679; Extensive experience with ETL/ELT tools and technologies (e.g., Apache Spark, Apache Kafka, SQL).&#9679; Strong proficiency in SQL and experience with various database systems, including:&#9675; Relational Databases: (e.g., PostgreSQL, SQL Server, Azure SQL Database).&#9675; NoSQL Databases: (e.g., MongoDB, Cassandra, Azure Cosmos DB).&#9675; Vector Databases: (e.g., Milvus, Pinecone, ChromaDB - understanding their data ingestion and retrieval aspects).&#9675; Graph Databases: (e.g., Neo4j, ArangoDB - understanding their data modeling and querying aspects).&#9679; Strong scripting and programming skills in languages such as Python or Scala for data processing and automation.&#9679; Experience with data governance frameworks, data quality management, and data security principles.&#9679; Experience with data monitoring and alerting tools.&#9679; Excellent problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues.&#9679; Strong collaboration and communication skills, with the ability to work effectively with Data Scientists, AI Engineers, AIOps/MLOps Engineers, and other stakeholders.&#9679; A proactive and detail-oriented approach with a strong focus on building robust and reliable data infrastructure.Bonus Points For:&#9679; Experience with data virtualization technologies.&#9679; Experience with building real-time data pipelines.&#9679; Knowledge of data lineage and data catalog tools (e.g., Azure Purview).&#9679; Experience with implementing data mesh concepts.&#9679; Familiarity with infrastructure-as-code (IaC) tools (e.g., Terraform, ARM templates) for data infrastructure provisioning.&#9679; Certifications in relevant cloud platforms or data engineering technologies.&#9679; Experience working with government data regulations and compliance standards.Job Type: Full-timePay: From AED20,000.00 per monthAbility to commute/relocate:<ul><li>Abu Dhabi: Reliably commute or planning to relocate before starting work (Required)</li></ul>Experience:<ul><li>data pipelines and data infra in a production env: 5 years (Required)</li><li>ETL/ELT tools and tech, Apache Spark, Apache Kafka, SQL: 5 years (Required)</li><li>AI/ML development : 3 years (Required)</li></ul>License/Certification:<ul><li>Emirates ID (Required)</li></ul>

Senior Data Engineer

Acenet consulting

About Us: AceNet Consulting is a fast-growing global business and technology consulting firm specializing in business strategy, digital transformation, technology consulting, product development, start-up advisory and fund-raising services to our global clients across banking &amp; financial services, healthcare, supply chain &amp; logistics, consumer retail, manufacturing, eGovernance and other industry sectors. We are looking for hungry, highly skilled and motivated individuals to join our dynamic team. If you&rsquo;re passionate about technology and thrive in a fast-paced environment, we want to hear from you.Role SummaryWe are seeking a highly experienced and technically strong Azure Technical Architect who will lead the design and implementation of enterprise cloud infrastructure and begin to integrate AI/ML capabilities. This role will require deep hands-on experience with infrastructure (on-prem/VMs/hybrid), extensive Azure cloud architectural experience, and a working knowledge of machine learning and AI so that you can partner with data science/ML teams and enable next-gen capabilities.Key Responsibilities<ul><li>Define and drive the technical architecture for Azure cloud (IaaS, PaaS, hybrid) infrastructure, ensuring alignment with business objectives, scalability, security, costoptimisation, reliability and operational excellence.</li><li>Lead design and deployment of Azure Landing Zones / enterprise cloud adoption frameworks and reference architectures (governance, subscriptions, management groups, identity, networking).</li><li>Hands-on design and implementation of infrastructure including compute (VMs, VM scale sets, containers/AKS), storage, databases, networking (VNet, peering, VPN/ExpressRoute, firewall, load balancers), identity &amp; access (Azure AD, RBAC, managed identities), hybrid connectivity.</li><li>Build and own Infrastructure as Code (IaC) modules/templates (e.g., Terraform, ARM, Bicep), CI/CD pipelines for infrastructure provisioning and deployments.</li><li>Lead and execute cloud migration strategies (on-prem &rarr; Azure, legacy workloads &rarr; cloud native), uplift existing systems, modernise infra, containerise where appropriate.</li><li>Ensure cloud security and compliance: enforce Azure best-practices, implement monitoring/logging (Azure Monitor, Log Analytics), guard-rails, cost governance, disaster recovery/business continuity, encryption, network segmentation.</li><li>AI/ML Integration: Work with data science/ML teams to architect and enable infrastructure and cloud services for ML/AI workloads&mdash;this includes responsible for enabling compute/data pipelines, containerisation, MLOps readiness, Azure ML, etc.</li><li>Provide technical leadership, mentoring and guidance to engineers, drive technical decision-making, perform architecture reviews, evaluate vendor/technology options.</li><li>Engage with stakeholders (business, IT leadership, external vendors) to understand requirements, create solution proposals, define technical roadmaps, present architecture, drive buy-in.</li><li>Establish and maintain architectural standards, patterns, reusable components, documentation (HLD/LLD, runbooks) and ensure their adoption.</li><li>Monitor and optimise Azure environment performance, cost, scalability and reliability over time &mdash; propose continuous improvement initiatives.</li><li>Stay current with emerging AI/ML trends and Azure services so you can guide future integration of AI capabilities into infrastructure/cloud platforms.</li></ul>Required Skills &amp; Experience<ul><li>10-15 years of total IT experience, with a strong technical focus and hands-on background in infrastructure, cloud, and architecture roles.</li><li>Deep practical experience with Microsoft Azure: IaaS, PaaS, containers (AKS), storage, databases, networking, identity &amp; access. (Design + implementation)</li><li>Strong infrastructure background: on-prem compute/virtualisation (VMware/HyperV), networking (TCP/IP, routing, firewalls), storage, hybrid connectivity.</li><li>Proven experience in designing and deploying cloud architectures (including hybrid/multi-cloud) for enterprise scale (large environments, many subscriptions, complex connectivity).</li><li>Proficiency with Infrastructure as Code (IaC) tools such as Terraform, ARM templates or Bicep &mdash; creating reusable modules and automating deployments.</li><li>Experience in DevOps / CI-CD / automation for infrastructure provisioning and integration with application delivery.</li><li>Strong skills in cloud networking (VNets, peering, VPN, ExpressRoute, NSG/ASG, firewalls), identity &amp; security (Azure AD, RBAC, managed identities, Key Vault) and governance (subscriptions, management groups, cost controls).</li><li>Basic AI/ML knowledge: Familiarity with machine learning fundamentals (supervised/unsupervised, feature engineering, model deployment concepts), and exposure to Azure ML or other equivalent services; able to collaborate with data/ML teams to enable infrastructure for ML.</li><li>Good communication and presentation skills &mdash; able to engage with senior stakeholders and translate business needs into technical architecture.</li><li>Proven track record of leading/mentoring technical teams, driving adoption of architecture and standards.</li><li>Relevant certifications such as Microsoft Certified: Azure Solutions Architect Expert (or equivalent) strongly preferred</li></ul>Why Join Us:<ul><li>Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors.</li><li>Continuous investment in employee growth and professional development with a strong focus on up &amp; re-skilling.</li><li>Competitive compensation &amp; benefits, ESOPs and international assignments.</li><li>Supportive environment with healthy work-life balance and a focus on employee well-being.</li><li>Open culture that values diverse perspectives, encourages transparent communication and rewards contributions.</li></ul>Job Types: Full-time, PermanentPay: AED350,000.00 - AED450,000.00 per yearLicense/Certification:<ul><li>Azure Solutions Architect Expert certification (Preferred)</li></ul>

Azure Technical Architect with AI-ML Knowledge

Explore 693+ Data scientist ai ml in Abu Dhabi With Doh Jobs In Abu Dhabi United Arab Emirates this November. Find roles across top companies and apply now to boost your career.