mechanical engineer

devops engineer

planning engineer

project engineer

ai engineer

platform engineer

D4 Insight

<div>Location: Abu Dhabi 
Experience: 7+ Years
<h3 class="jobSectionHeader">
Role Overview:</h3>

The Azure Platform Engineer will design and operate enterprise Azure environments supporting AI-driven applications and banking platforms.
<h3 class="jobSectionHeader">
Key Responsibilities:</h3>
<ul><li>Build Azure landing zones.</li>
<li>Implement Terraform-based automation.</li>
<li>Integrate Azure OpenAI and AI Search services.</li>
<li>Manage APIM, networking, and cloud operations.</li>
<li>Drive FinOps and cloud optimization initiatives.</li>
</ul><h3 class="jobSectionHeader">Required Skills:</h3>
<ul><li>Azure</li>
<li>Terraform</li>
<li>Azure OpenAI</li>
<li>AI Search</li>
<li>APIM</li>
<li>FinOps</li>
<li>CI/CD</li>
</ul>
 Apply Now: [email protected]</div>

Senior Platform Engineer (Azure Focus)

Fecundity Technologies

Role Overview: We are looking for a Senior Platform Engineer to design, build, and scale Azure cloud and hybrid-cloud ecosystems from the ground up for a large Financial Enterprise. You will be responsible for creating a robust foundation for our application teams, with a specific focus on operationalizing AI services, maintaining rigorous security standards, and optimizing cloud spend through FinOps best practices.Key Responsibilities:<ul><li>Greenfield Infrastructure: Architect and deploy production-ready Azure environments from scratch using a landing zone approach.</li><li>AI Orchestration: Integrate and manage Azure AI services (OpenAI, AI Search, Document Intelligence, Content Safety) to support AI-driven application development.</li><li>Infrastructure as Code: Standardize all deployments using Terraform to ensure consistency and modularity.</li><li>API &amp; Connectivity: Manage API lifecycles using Azure APIM and Kong, ensuring secure and performant communication between services.</li><li>FinOps &amp; Monitoring: Proactively manage cloud costs by analyzing SKUs and implementing advanced monitoring/alerting to prevent budget overruns.</li><li>Automation: Design automated GitHub Workflows to enable seamless CI/CD for both infrastructure and application code.</li></ul>Technical Requirements:<ul><li>Cloud: 8+ years experience with Azure Cloud Platform.</li><li>IaC: Expert-level Terraform skills.</li><li>AI Stack: Familiarity with Azure AI Foundry and OpenAI Service.</li><li>Networking: Expert knowledge of Network Architecture (VNETs, Peering, Firewalls, Private Links).</li><li>APIs: Hands-on experience with Azure APIM or Kong.</li></ul>Deployment Architecture: Proven ability to create professional Cloud Architecture Diagrams and provide Solutions Architecture guidance.Pay: AED26,000.00 - AED31,000.00 per monthApplication Question(s):<ul><li>Which tools or approaches have you used for monitoring and alerting (Azure Monitor, Log Analytics, etc.)?</li><li>Have you worked in environments with strict cost governance or quotas?</li><li>Have you created cloud architecture diagrams and presented solutions to stakeholders?</li><li>Describe a complex cloud architecture you designed (include security, scalability, and reliability considerations).</li></ul>Work Location: In person

Lead AI Cloud Platform Engineer (Banking Industry)

Role Overview: We are looking for a Senior Platform Engineer to design, build, and scale Azure cloud and hybrid-cloud ecosystems from the ground up for a large Financial Enterprise. You will be responsible for creating a robust foundation for our application teams, with a specific focus on operationalizing AI services, maintaining rigorous security standards, and optimizing cloud spend through FinOps best practices.Key Responsibilities:<ul><li>Greenfield Infrastructure: Architect and deploy production-ready Azure environments from scratch using a landing zone approach.</li><li>AI Orchestration: Integrate and manage Azure AI services (OpenAI, AI Search, Document Intelligence, Content Safety) to support AI-driven application development.</li><li>Infrastructure as Code: Standardize all deployments using Terraform to ensure consistency and modularity.</li><li>API &amp; Connectivity: Manage API lifecycles using Azure APIM and Kong, ensuring secure and performant communication between services.</li><li>FinOps &amp; Monitoring: Proactively manage cloud costs by analyzing SKUs and implementing advanced monitoring/alerting to prevent budget overruns.</li><li>Automation: Design automated GitHub Workflows to enable seamless CI/CD for both infrastructure and application code.</li></ul>Technical Requirements:<ul><li>Cloud: 5+ years experience with Azure Cloud Platform.</li><li>IaC: Expert-level Terraform skills.</li><li>AI Stack: Familiarity with Azure AI Foundry and OpenAI Service.</li><li>Networking: Expert knowledge of Network Architecture (VNETs, Peering, Firewalls, Private Links).</li><li>APIs: Hands-on experience with Azure APIM or Kong.</li></ul>Deployment Architecture: Proven ability to create professional Cloud Architecture Diagrams and provide Solutions Architecture guidance.Pay: AED18,000.00 - AED24,000.00 per monthApplication Question(s):<ul><li>How many years of hands-on experience do you have with Microsoft Azure?</li><li>Have you built an Azure environment from scratch (Greenfield / Landing Zone approach)?</li><li>Please provide an example of a complex Terraform module you&rsquo;ve built.</li><li>Do you have hands-on experience with Azure AI services (OpenAI, AI Search, Document Intelligence, etc.)?</li><li>How do you monitor and optimize Azure cloud costs?</li><li>Which tools or approaches have you used for monitoring and alerting (Azure Monitor, Log Analytics, etc.)?</li></ul>Work Location: In person

Sr. AI Cloud Platform Engineer – Azure (Banking Industry)

<div>
 
 Location:
 
 Abu Dhabi
 
 
 
 Experience:
 
 5+ Years
 
 
 
 Role Overview
 
 
 
 The DevOps Engineer will manage deployment automation, cloud infrastructure, Kubernetes operations, and platform reliability across Azure-based AI environments.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Build Infrastructure as Code using Terraform and Bicep.
 </li>
 <li>
 Manage AKS environments and Kubernetes operations.
 </li>
 <li>
 Implement CI/CD pipelines.
 </li>
 <li>
 Support monitoring, DR, and security controls.
 </li>
 <li>
 Maintain platform reliability and scalability.
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 <ul>
 <li>
 Azure
 </li>
 <li>
 AKS
 </li>
 <li>
 Terraform
 </li>
 <li>
 Bicep
 </li>
 <li>
 Kubernetes
 </li>
 <li>
 CI/CD
 </li>
 <li>
 DevOps Automation
 
 
 </li>
 </ul>
 📩
 
 Apply Now: careers@d4insight.com
 
</div>

DevOps Engineer

ENEC Operations

<div>
 
 The Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance &amp; Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.
 
 
 
 
 
 The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.
 
 
 Activity: Data Engineering Architecture &amp; Platform Development
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
 
 
 &bull; Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools.
 
 
 &bull; Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs.
 
 
 &bull; Ensure seamless integration of OT and industrial data sources &mdash; including PI System, SCADA, and DCS &mdash; into enterprise data platforms.
 
 
 &bull; Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption.
 
 
 &bull; Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements.
 
 
 &bull; Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML.
 
 
 &bull; Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining &mdash; ensuring reliability and reproducibility.
 
 
 &bull; Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio.
 
 
 &bull; Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization.
 
 
 &bull; Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance.
 
 
 &bull; Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards.
 
 
 &bull; Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.
 
 
 Activity: Advanced Subject Matter Knowledge
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments.
 
 
 &bull; Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements.
 
 
 &bull; Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning.
 
 
 &bull; Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management.
 
 
 &bull; Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments.
 
 
 &bull; Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.
 
 
 Activity: Complex Problem Solving &amp; Innovation
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration &mdash; delivering innovative, compliant, and production-ready solutions.
 
 
 &bull; Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions.
 
 
 &bull; Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges.
 
 
 &bull; Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes.
 
 
 &bull; Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.
 
 
 &bull; Leads proof-of-concept and pilot initiatives to evaluate new data and AI technologies and engineering approaches
 
 
 
 
 
 Activity: Applied Skills &amp; Professional Know-How
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Expertly engineers, deploys, and operates scalable, secure, and compliant data and AI platforms across Databricks, Azure, and OT environments.
 
 
 &bull; Applies hands-on proficiency in building data pipelines, ML models, GenAI solutions, BI semantic models, and governance frameworks in production environments.
 
 
 &bull; Mentors and develops junior and mid-level data engineers, data scientists, and analytics engineers &mdash; building future-ready technical capabilities.
 
 
 &bull; Leads technical design reviews, code reviews, and architecture assessments to uphold engineering quality and best practices.
 
 
 &bull; Effectively translates complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
 
 
 &bull; Documents solutions, engineering patterns, and technical standards to build institutional knowledge and enable knowledge transfer.
 
 
 Activity: Security, Governance &amp; Compliance
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design and enforce data security, access control, and privacy frameworks across all data and AI platforms using Unity Catalog, Collibra, and Azure security controls.
 
 
 &bull; Ensure all data engineering and AI solutions comply with national and international nuclear regulations, FANR requirements, and Responsible AI principles.
 
 
 &bull; Maintain comprehensive data lineage, audit trails, and documentation to support regulatory, audit, and governance requirements.
 
 
 &bull; Implement and enforce data quality frameworks and data governance policies using Collibra Data Quality and Unity Catalog.
 
 
 &bull; Conduct regular platform security assessments, data quality audits, and compliance reviews.
 
 
 &bull; Oversee risk management, audit readiness, and the implementation of robust technical controls for all platform operations.
 
 
 
 
 
 
 
 
 
 Minimum
 
 
 
 &bull; Bachelor&rsquo;s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.
 
 
 &bull; Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations.
 
 
 &bull; Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.
 
 
 
 
 
 
 
 
 
 Preferred
 
 
 
 
 
 
 &bull; Master&rsquo;s degree in a relevant field.
 
 
 &bull; Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors.
 
 
 &bull; Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in data bricks or similar AI/analytics platforms exposure.
 
 
 &bull; Demonstrated experience leading large-scale data and AI engineering programs
 
 
 
 
 
 
 
 
 
 Certification -
 
 
 
 
 
 
 Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.
 
 
 
 
 
 Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).
 
</div>

Data and AI Engineering Expert

<div>
 
 Job Description
 
 
 
 
 Location:
 
 Abu Dhabi
 
 
 
 Experience:
 
 5&ndash;8 Years
 
 
 
 Role Overview
 
 
 
 We are looking for skilled Site Reliability Engineer with experience in Wealth Management and Brokerage platforms to ensure system reliability, scalability, and operational excellence.
 
 
 The role combines software engineering, cloud infrastructure, application support, and FinTech platform operations.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Support wealth and brokerage applications.
 </li>
 <li>
 Manage cloud infrastructure on AWS and Azure.
 </li>
 <li>
 Build and maintain CI/CD pipelines.
 </li>
 <li>
 Support APIs, microservices, and distributed systems.
 </li>
 <li>
 Manage databases and application integrations.
 </li>
 <li>
 Drive incident and problem management activities.
 </li>
 <li>
 Monitor emerging FinTech technologies and innovations.
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 <ul>
 <li>
 Wealth &amp; Brokerage Platforms
 </li>
 <li>
 AWS &amp; Azure
 </li>
 <li>
 Java &amp; .NET Core
 </li>
 <li>
 Docker &amp; Kubernetes
 </li>
 <li>
 CI/CD &amp; DevOps
 </li>
 <li>
 APIs &amp; Microservices
 </li>
 <li>
 Incident Management
 
 
 </li>
 </ul>
 📩
 
 Apply Now: careers@d4insight.com
 
 
 
 Job Details
 
 
 Role Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Abu Dhabi Company Website: http://www.d4insight.com/ Job Function: DevOps &amp; QA Company Industry/
 
 
 Sector: Information Technology and Services
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
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</div>

Site Reliability Engineer SRE Wealth And Brokerage

Contango

<div>
 
 Contract duration:
 
 6 months (with a potential extension)
 
 
 
 Engagement Type:
 
 Full-time
 
 
 
 Start date:
 
 July 2026
 
 
 
 Location:
 
 Abu Dhabi (on-site)
 
 
 
 Role Overview
 
 
 
 We are seeking an experienced DevOps Engineer to make software delivery fast, repeatable, and safe. You&rsquo;ll build and operate CI/CD pipelines, infrastructure-as-code, container platforms, and observability &mdash; cutting lead time and toil while improving reliability and security.
 
 
 The discipline has shifted toward platform engineering: building internal developer platforms and golden paths so product teams can self-serve, with GitOps, policy-as-code, and supply-chain security built in. DevSecOps and FinOps are core parts of the job here, not afterthoughts.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and maintain CI/CD pipelines with automated testing, security scanning, and progressive delivery.
 </li>
 <li>
 Author infrastructure as code with Terraform/OpenTofu using reusable modules and clean environment promotion.
 </li>
 <li>
 Build and operate Kubernetes platforms &mdash; Helm/Kustomize packaging, autoscaling, and ingress.
 </li>
 <li>
 Implement GitOps with Argo CD or Flux so the desired state of infrastructure and apps lives in Git.
 </li>
 <li>
 Stand up observability: metrics, logs, traces, dashboards, SLOs, and alerting.
 </li>
 <li>
 Embed DevSecOps: SAST/DAST/SCA scanning, secrets management, image hardening, and software supply-chain security.
 </li>
 <li>
 Build internal developer platforms and golden paths that enable self-service for product teams.
 </li>
 <li>
 Manage cloud infrastructure with cost awareness, automate operational tasks, and improve DORA metrics; participate in on-call and run blameless post-mortems.
 
 
 </li>
 </ul>
 
 Candidate Requirements
 
 
 
 <ul>
 <li>
 Demonstrated experience delivering AI solutions in an enterprise or client-facing/consulting environment.
 </li>
 <li>
 Prior experience at management consulting firms and/or Big Tech is an advantage.
 </li>
 <li>
 Bachelor's or Master&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field.
 </li>
 <li>
 3+ years in DevOps, SRE, platform, or infrastructure engineering.
 </li>
 <li>
 Strong Linux fundamentals and scripting in Bash and Python (Go a plus).
 </li>
 <li>
 Production experience with a major cloud (AWS, Azure, or GCP).
 </li>
 <li>
 Hands-on experience running Docker and Kubernetes in production.
 </li>
 <li>
 Proficiency with infrastructure as code (Terraform/OpenTofu) and a CI/CD system (GitHub Actions, GitLab CI, or Jenkins).
 </li>
 <li>
 Solid grasp of networking, DNS, TLS, load balancing, and security fundamentals.
 </li>
 <li>
 Experience with monitoring/observability tooling and incident management.
 
 
 </li>
 </ul>
 
 Nice To Have
 
 
 
 <ul>
 <li>
 Operating ML/AI infrastructure (GPU clusters, model serving, MLOps/LLMOps pipelines).
 </li>
 <li>
 Multi-cloud or hybrid-cloud architecture and migrations.
 </li>
 <li>
 Chaos engineering and advanced reliability practices.
 </li>
 <li>
 eBPF-based tooling (Cilium, Pixie) and custom Kubernetes operators.
 </li>
 <li>
 Certifications such as CKA/CKAD, a cloud architect cert, or Terraform Associate.
 
 
 </li>
 </ul>
 
 Tools &amp; Technologies You&rsquo;ll Work With
 
 
 
 <ul>
 <li>
 Scripting: Bash, Python, Go; YAML, HCL.
 </li>
 <li>
 CI/CD: GitHub Actions, GitLab CI, Jenkins, Azure DevOps.
 </li>
 <li>
 IaC &amp; config: Terraform/OpenTofu, Pulumi, Ansible, Crossplane.
 </li>
 <li>
 Containers &amp; GitOps: Docker, Kubernetes, Helm, Kustomize, Argo CD, Flux, Argo Rollouts.
 </li>
 <li>
 Observability: Prometheus, Grafana, OpenTelemetry, Loki, ELK/OpenSearch, Datadog.
 </li>
 <li>
 DevSecOps: Trivy, Snyk, SonarQube, Checkov, OPA/Kyverno; Sigstore, SLSA, SBOMs.
 </li>
 <li>
 Secrets &amp; platform: HashiCorp Vault, External Secrets, OIDC workload identity; Backstage; AWS, Azure, GCP.
 </li>
 </ul>
</div>

DevOps Engineer (6 months contract)

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