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azure devops (data) engineer - Jobs in Abu Dhabi

azure devops (data) engineer -

devops engineer

Mind Stream

Job location: Doha, QatarJob description:Proven experience with Azure DevOps and implementing CI/CD pipelines.<ul><li>Strong knowledge of Azure data services, specifically Azure Databricks and Azure Data Factory.</li><li>Proficiency in Databricks Asset Bundle for Databricks Ci/CD.</li><li>Experience with scripting and automation tools (e.g., PowerShell, Python).</li><li>Experience in implementing selective deployment for ADF data pipelines.</li><li>Understanding of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.</li><li>Excellent problem-solving skills and ability to troubleshoot complex CI/CD issues.</li><li>Strong communication skills and ability to collaborate effectively with cross-functional teams.</li><li>Knowledge of security best practices for CI/CD pipelines and Azure environments.</li><li>Detail-oriented with a focus on delivering high-quality, reliable automation solutions.</li><li>Bachelor's degree in Computer Science, Information Technology, or related field.</li><li>Minimum of 5 years of experience in DevOps or related roles.</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Have you worked with Azure Databricks and Azure Data Factory (ADF)?</li><li>Are you familiar with Databricks Asset Bundle for Databricks CI/CD?</li><li>How many years of experience do you have with Python or PowerShell scripting?</li><li>Have you implemented selective deployment for ADF pipelines?</li><li>What is your current and expected salary?</li><li>What is your notice period or earliest joining availability?</li></ul>

Azure DevOps (Data) Engineer -

JCA Associates

<div>
 
 🚀
 
 Senior Technical Site Engineer &ndash; Abu Dhabi (On-Site)
 
 
 
 
 Join a global leader shaping the future of autonomous airspace
 
 
 
 
 
 
 We&rsquo;re expanding our engineering operations in the United Arab Emirates and are looking for a
 
 Senior Technical Site Engineer
 
 to take a key role in supporting mission-critical drone fleet management and UAS traffic management systems.
 
 
 
 
 
 This is a high-impact, hands-on technical role where you&rsquo;ll serve as the
 
 Tier-3 escalation point
 
 , working directly with engineering teams across R&amp;D, DevOps, and Product to ensure reliability, stability, and world-class performance across real-time systems.
 
 
 If you thrive in fast-moving environments, enjoy solving complex technical problems, and want to be part of one of the most exciting and high-growth sectors in aviation technology &mdash; we&rsquo;d love to speak with you.
 
 
 
 
 
 🔧
 
 What You&rsquo;ll Be Doing
 
 
 <ul>
 <li>
 Act as the senior technical point of contact for advanced production issues
 </li>
 <li>
 Lead deep-dive investigations using
 
 Prometheus, Grafana, and Kibana
 
 </li>
 <li>
 Analyze logs, identify root causes, and drive long-term fixes
 </li>
 <li>
 Support Kubernetes-based microservices and cloud environments (G42 or AWS)
 </li>
 <li>
 Create scripts, automation, and quick hotfixes when required
 </li>
 <li>
 Manage local release cycles and deployments across the UAE
 </li>
 <li>
 Collaborate with global engineering teams to drive technical improvements
 </li>
 <li>
 Represent engineering in customer discussions, demos, and operational events
 </li>
 <li>
 Mentor on-site technical staff and help define local support processes
 </li>
 </ul>
 
 
 
 
 🎯
 
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 5+ years in
 
 Backend Engineering / DevOps / SRE / Tier-3 Support
 
 </li>
 <li>
 Strong experience with
 
 Node.js
 
 and
 
 MongoDB
 
 </li>
 <li>
 Hands-on Kubernetes experience in production
 </li>
 <li>
 Familiarity with
 
 RabbitMQ
 
 or similar message brokers
 </li>
 <li>
 Skilled with observability tooling (Prometheus/Grafana/Kibana)
 </li>
 <li>
 Experience with cloud infrastructure (G42 preferred, AWS accepted)
 </li>
 <li>
 Strong debugging, incident analysis, and scripting ability
 </li>
 <li>
 Ability to work independently and manage complex technical scenarios
 </li>
 <li>
 Comfortable interfacing with customers and representing engineering teams
 </li>
 <li>
 Experience in mission-critical or regulated industries is a strong advantage
 </li>
 </ul>
 
 
</div>

Technical Engineer

Drivys

We Are Hiring &ndash; Senior Golang DeveloperWe are looking for a highly skilled Senior Golang Developer with strong experience in Flutter and DevOps to join our tech team and work on scalable, high-performance systems.Requirements:5+ years of hands-on experience with GolangStrong knowledge of microservices architectureExperience with RESTful APIs, gRPC, and high-performance backend systemsSolid experience with Flutter (Android &amp; iOS)Good understanding of DevOps practices (CI/CD, Docker, cloud deployments)Familiarity with SQL/NoSQL databasesExperience working with containerized environments (Docker, cloud services)Ability to lead technical decisions and mentor junior developersRole Responsibilities:Design and build robust backend services using GoDevelop and maintain mobile applications using FlutterImplement and improve CI/CD pipelines and DevOps workflowsOptimize overall system performance, scalability, and reliabilityCollaborate with cross-functional teams to deliver high-quality solutionsParticipate in architecture planning and contribute to technical leadershipJob Type: Full-timeApplication Question(s):<ul><li>How much your current salary?</li></ul>

Sr. Golang Developer

NeST Digital

<div><div>Minimum Required Experience : 6 years
Full Time
</div><div><div>Skills<div><div><div><div>
Bare Metal Programming</div></div><div><div>
Linux</div></div><div><div>
Communications Protocols</div></div><div><div>
Embedded C++</div></div><div><div>
RTOS</div></div></div></div></div></div><div>
Description<div>
Job Description &ndash; Senior Software Engineer
Experience Range
6 - 8 YOE
Location Requirement
Bangalore &ndash; PSN, Whitefield
Mode
Hybrid (3 days a week)
Responsibilities
<ul><li>Provide technology contributions in
<ul><li>Working in an agile development environment, Scrum, Iterative, V-mode</li>
<li>Translating business requirements into low-level application design</li>
<li>Application code development through a collaborative approach</li>
<li>Doing Full-scale unit testing</li>
<li>Embedded SW Design, development, test &amp; integration, debugging techniques.</li>
<li>Object oriented analysis and design, Design Patterns</li>
</ul></li></ul>Soft Skills
<ul><li>Should be able to contribute as an individual contributor</li>
<li>Should be able to execute his/her responsibility independently</li>
<li>Excellent problem-solving skills and attention to detail.</li>
<li>Focus on self-planning activities</li>
<li>Firm with communication skills</li>
<li>Organize and present technical status to Technical Leader.</li>
</ul>
Mandatory Skills
<ul><li>C++[OOPS]</li>
<li>Good understanding of OS: Linux, RTOS</li>
<li>Experience on IDE : Tornado, Visual Studio</li>
<li>Good understanding of Networking Protocols: TCP/IP Layer, Client Server Architectures</li>
<li>Exposure to IPC, I2C, UART, USB, Ethernet, SPI, , Wireless Technologies (BLE)</li>
<li>Good understanding of stacks, memory mngt, heaps, multithreading, memory profiling tools like Coverity, Valgrind</li>
<li>Good Experience in Bare metal programming &amp; debugging techniques.</li>
<li>Experience on Gerrit/Git/Jenkins/GitBucket and CI build process</li>
</ul>
Nice-to-have Skills
<ul><li>Exposure to Medical Standards &amp; Protocols: EMR, HL7, FHIR, MLLP, IoT device-cloud connectivity protocols such as MQTT, COAP, WebSockets.</li>
<li>Experience in Healthcare domain is a plus</li>
<li>C language programming skills</li>
<li>Good in Scripting Languages: Python, Makefiles, CMake</li></ul></div></div></div>

Lead Engineer-API/Cloud/DevSecOps Engineer

KATIM

<div>
 
 About KATIM
 
 
 
 KATIM is a leader in the development of innovative secure communication products and solutions for governments and businesses. As part of the Space &amp; Cyber Technologies cluster at EDGE, one of the world&rsquo;s leading advanced technology groups, KATIM delivers trust in a world where cyber risks are a constant threat, and fulfils the increasing demand for advanced cyber capabilities by delivering robust, secure, end-to-end solutions centered on four core business units: Networks, Ultra Secure Mobile Devices, Applications, and Satellite Communications. Our talented team of cross functional experts continually takes-on new challenges. We work with the energy of a start-up yet the discipline of a large business to make solutions and products work for our customers at scale.
 
 
 
 Job Purpose (specific To This Role)
 
 
 
 The Principal MLOps Engineer / AI Infrastructure Architect defines and leads the design, automation, and governance of KATIM&rsquo;s AI infrastructure powering mission-critical, secure communications products. This role drives end-to-end MLOps strategy &mdash; from model governance and deployment automation to compliance enforcement &mdash; ensuring every AI capability adheres to zero-trust and sovereign-data principles. This role bridges applied machine learning, software engineering, and DevSecOps &mdash; ensuring that AI models, pipelines, and applications are deployed, monitored, and scaled securely across environments.
 
 
 You will operate in an AI-augmented product development environment, where infrastructure provisioning, model training, deployment, and monitoring are automated or AI-assisted. Your mission is to build systems that empower product teams to deliver production-grade AI capabilities with the speed, reliability, and compliance standards required by government and enterprise clients.
 
 
 You will collaborate closely with cross-functional teams across platform engineering, product security, and product management to design MLOps pipelines that embody resilience, traceability, and zero-trust security principles. This role is ideal for engineers passionate about building intelligent automation frameworks, scalable AI pipelines, and secure data infrastructures that form the foundation of mission-critical AI systems.
 
 
 
 AI-Augmented Product Development Model (Context for the Role)
 
 
 
 We are a lean, AI-augmented product development team delivering production-ready, enterprise-grade secure applications with the quality and velocity typically requiring 3&ndash;4x larger organizations. Every role in the traditional SDLC is either AI-augmented or automated, allowing teams to focus on design, architecture, and high-impact decision-making.
 
 
 
 Core Principles
 
 
 
 <ul>
 <li>
 Security is integrated into every decision, from architecture to deployment.
 </li>
 <li>
 Repetitive tasks are automated; human effort is focused on strategy and problem-solving.
 </li>
 <li>
 Quality is measurable, enforced, and automated at every stage.
 </li>
 <li>
 All system behaviors&mdash;including AI-assisted outputs&mdash;must be traceable, reviewable, and explainable. We do not ship &ldquo;black box&rdquo; functionality.
 </li>
 <li>
 Design and implementation decisions prioritize resilience, maintainability, and interoperability in real customer environments.
 
 
 </li>
 </ul>
 
 Key Responsiblities
 
 
 
 AI MLOps Architecture &amp; Governance (30%)
 
 
 <ul>
 <li>
 Define the MLOps architecture and governance framework across products.
 </li>
 <li>
 Design secure, scalable AI platform blueprints covering data, training, serving and monitoring layers.
 </li>
 <li>
 Standardize model registries, artifact signing, and deployment processes for air-gapped and on-prem environments.
 </li>
 <li>
 Lead architectural designs and reviews for AI pipelines.
 </li>
 <li>
 Design and maintain LLM inference infrastructure
 </li>
 <li>
 Manage model registries and versioning (MLflow, Weights &amp; Biases)
 </li>
 <li>
 Implement model serving solutions (TensorFlow Serving, TorchServe, vLLM)
 </li>
 <li>
 Optimize model performance and cost (quantization, caching, batching)
 </li>
 <li>
 Build and maintain vector databases (Pinecone, Weaviate, Chroma)
 </li>
 <li>
 Hardware and inference optimization awareness
 
 
 </li>
 </ul>
 Agent &amp; Tool Development (25%)
 
 
 <ul>
 <li>
 Develop and maintain AI agents for automation (e.g., automated test generation, log intelligence, and anomaly detection).
 </li>
 <li>
 Build AI-assisted DevSecOps utilities to automatically enforce compliance, logging, and audit policies.
 </li>
 <li>
 Build tool integrations for LLM agents (function calling, APIs)
 </li>
 <li>
 Implement retrieval-augmented generation (RAG) pipelines
 </li>
 <li>
 Create prompt management and versioning systems
 </li>
 <li>
 Monitor and optimize agent performance
 
 
 </li>
 </ul>
 CI/CT/CD Pipelines (20%)
 
 
 <ul>
 <li>
 Build continuous integration pipelines for models and code
 </li>
 <li>
 Implement continuous training (CT) workflows
 </li>
 <li>
 Automate model deployment with rollback capabilities
 </li>
 <li>
 Create staging and production deployment strategies
 </li>
 <li>
 Integrate AI-assisted code review into CI/CD
 </li>
 <li>
 Building a continuous evaluation loop
 
 
 </li>
 </ul>
 Infrastructure &amp; Automation (15%)
 
 
 <ul>
 <li>
 Manage cloud infrastructure (Kubernetes, serverless)
 </li>
 <li>
 Implement Infrastructure as Code (Terraform, Pulumi)
 </li>
 <li>
 Build monitoring and observability systems (Prometheus, Grafana, DataDog)
 </li>
 <li>
 Automate operational tasks with AI agents
 </li>
 <li>
 Ensure security and compliance (OWASP, SOC2) - AI-specific security
 
 
 </li>
 </ul>
 Developer Enablement (10%)
 
 
 <ul>
 <li>
 Provide tools and libraries for engineers to adopt AI-augmented workflows securely.
 </li>
 <li>
 Document AI/ML best practices and patterns
 </li>
 <li>
 Conduct training on MLOps tools and workflows
 </li>
 <li>
 Support engineers with AI integration challenges
 </li>
 <li>
 Maintain development environment parity
 </li>
 <li>
 AI Privacy, Governance, and Compliance
 
 
 </li>
 </ul>
 
 Education and Minimum Qualification
 
 
 
 <ul>
 <li>
 BS in Computer Science, Computer Engineering, Mathematics or related field, or equivalent experience in industry / Masters preferred.
 </li>
 <li>
 8+ years in DevOps, SRE, or platform engineering
 </li>
 <li>
 5+ years hands-on experience with ML/AI systems in production
 </li>
 <li>
 Deep understanding of LLMs and their operational requirements
 </li>
 <li>
 Experience building and maintaining CI/CD pipelines
 </li>
 <li>
 Strong Linux/Unix systems knowledge
 </li>
 <li>
 Cloud platform expertise (AWS, GCP, or Azure)
 </li>
 <li>
 Experience with container orchestration (Kubernetes)
 
 
 </li>
 </ul>
 
 Key Skills
 
 
 
 MLOps &amp; AI:
 
 
 <ul>
 <li>
 LLM Integration: OpenAI API, Anthropic API, HuggingFace, Azure OpenAI
 </li>
 <li>
 Model Serving: TensorFlow Serving, TorchServe, vLLM, Ollama
 </li>
 <li>
 Experiment Tracking: MLflow, Weights &amp; Biases, Neptune.ai
 </li>
 <li>
 Model Registries: MLflow, Kubeflow, AWS SageMaker
 </li>
 <li>
 Vector Databases: Pinecone, Weaviate, Chroma, Milvus
 </li>
 <li>
 Agent Frameworks: LangChain, LlamaIndex, AutoGPT, Semantic Kernel
 </li>
 <li>
 Fine-tuning: LoRA, QLoRA, prompt tuning
 
 
 </li>
 </ul>
 Data Engineering:
 
 
 <ul>
 <li>
 Pipelines: Airflow, Prefect, Dagster
 </li>
 <li>
 Processing: Spark, Dask, Ray
 </li>
 <li>
 Streaming: Kafka, Pulsar, Kinesis
 </li>
 <li>
 Data Quality: Great Expectations, dbt
 </li>
 <li>
 Feature Stores: Feast, Tecton
 
 
 </li>
 </ul>
 DevOps &amp; Infrastructure:
 
 
 <ul>
 <li>
 Containers: Docker, Kubernetes, Helm
 </li>
 <li>
 Cloud Platforms: AWS (SageMaker, Lambda, ECS) OR GCP (Vertex AI, Cloud Run) OR Azure (ML Studio)
 </li>
 <li>
 IaC: Terraform, Pulumi, CloudFormation
 </li>
 <li>
 CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD
 </li>
 <li>
 Orchestration: Kubernetes operators, Kubeflow
 
 
 </li>
 </ul>
 Monitoring &amp; Observability:
 
 
 <ul>
 <li>
 Metrics: Prometheus, Grafana, CloudWatch
 </li>
 <li>
 Logging: ELK Stack, Loki, CloudWatch Logs
 </li>
 <li>
 Tracing: Jaeger, Zipkin, OpenTelemetry
 </li>
 <li>
 Alerting: PagerDuty, Opsgenie
 </li>
 <li>
 Model Monitoring: Arize, Fiddler, Evidently
 
 
 </li>
 </ul>
 Programming:
 
 
 <ul>
 <li>
 Python: Primary language for ML/AI
 </li>
 <li>
 Libraries: NumPy, Pandas, PyTorch/TensorFlow, scikit-learn
 </li>
 <li>
 FastAPI, Flask for serving
 </li>
 <li>
 Go: For high-performance services and tooling
 </li>
 <li>
 Shell Scripting: Bash, Python for automation
 </li>
 <li>
 SQL: Advanced queries, optimization
 
 
 </li>
 </ul>
 AI-Assisted Operations:
 
 
 <ul>
 <li>
 Autonomous agents for incident response
 </li>
 <li>
 AI-powered log analysis and anomaly detection
 </li>
 <li>
 Automated root cause analysis
 </li>
 <li>
 Intelligent alerting and noise reduction
 
 
 </li>
 </ul>
 Other Highly Desirable Skills:
 
 
 <ul>
 <li>
 Experience with LLM fine-tuning and deployment at scale
 </li>
 <li>
 Background in data engineering or ML engineering
 </li>
 <li>
 Startup or high-growth environment experience
 </li>
 <li>
 Security certifications (CISSP, AWS Security)
 </li>
 <li>
 Contributions to open source MLOps projects
 </li>
 <li>
 Experience with multi-cloud or hybrid cloud
 </li>
 <li>
 Prior software engineering experience
 
 
 </li>
 </ul>
 
 Success Metrics
 
 
 
 <li>
 Uptime: 99.9%+ availability for AI services
 </li>
 <li>
 Deployment Frequency: Daily or on-demand deployments
 </li>
 Model Performance: Latency (p95 &lt; 500ms), accuracy tracking
 <li>
 Cost Efficiency: Cost per inference, infrastructure utilization
 </li>
 <li>
 Developer Velocity: Time to deploy new models, AI feature adoption rate
 </li>
 <li>
 Incident Response: MTTD (Mean Time to Detect), MTTR (Mean Time to Resolve)
 
 
 </li>
 
 #KATIM
 
</div>

Principal Engineer - ML Ops

DICETEK LLC

<div>Minimum Experience
&sect; At least 10+ years of experience in software engineering, API development, AWS Lamba development, DevOps and automation tools.
&sect; Hands on Experience in Software Development Life Cycle
&sect; Strong experience in Openbanking.
&sect; Strong knowledge and experience in API development, AWS Lamba development, Kubernetes, Docker, and other container technologies.
&sect; Strong knowledge and experience in Gitlab, Nexus and other similar tools.
&sect; Experience in continuous Monitoring, troubleshoot, and optimize the performance and availability of the APIs using AppDynamics, ELK and other observability tools.
&sect; Experience in delivering best quality code ensuring delivery of security vulnerable free implementations.
&sect; Experience in working with agile methodologies and cross-functional teams.
&sect; Excellent communication, collaboration, and problem-solving skills.
&sect; Passion for learning and innovation.
&sect; Ability to work independently and as part of a team.
&sect; Knowledge of scripting languages, such as Python or similar other ones.
&sect; Ability to coach and guide the team of Engineers or other Service Management Staff
&sect; Ability to identify requirements and create a solution architecture that meets identified requirements.
&sect; Proficiency in troubleshooting issues, troubleshooting using tools or debugging a large codebase.
&sect; Identifies and evaluates new technologies for implementation.
&sect; Strong analytical and reasoning skills with an ability to visualize processes and outcomes.
&sect; Experience in use of Performance measuring tools for analysing Performance and hot-spots to further fine tune the implementations to deliver performant implementations
&sect; Continually improves system monitoring and alerting.
&sect; Identifies and fixes the security vulnerabilities.
&sect; Practical knowledge of DevSecOps Model.
&sect; Extensive experience in software engineering, with a focus on API development, including RESTful and SOAP APIs, using Java Springboot framework and Maven.
&sect; Experience with API management and governance tools such as Apigee, Kong, or AWS API Gateway.
&sect; Experience with API security and authentication protocols such as OAuth, JWT, or API keys
&sect; Nice to have knowledge / experience in Python, Node.JS
&sect; Proficiency in design tools such as Visio, Draw.io
&sect; Proven track record of designing and implementing complex API solutions in large-scale environments, particularly within the financial sector.
&sect; Strong understanding of API security practices and governance, including experience with tools like Swagger, Postman, AppDynamics, ELK, and other observability tools.
&sect; Leadership skills to mentor junior engineers and lead cross-functional teams.
&sect; Knowledge of API management tools and platforms to support governance processes.
&sect; Ability to document and maintain API specifications and standards.
&sect; Experience in monitoring and optimizing API performance.
&sect; Research skills to evaluate new technologies and trends in API implementation.
&sect; Strong communication skills to collaborate with other developers, product owners, and stakeholders.
Capability to implement API governance documents recommended by FAB, ensuring alignment with strategic objectives and regulatory requirements.</div>

Principal Software Engineer / Lead API developer

Explore 442+ Devops engineer in Abu Dhabi this December. Find roles across top companies and apply now to boost your career.

442 devops engineer jobs IN Abu Dhabi

Azure DevOps (Data) Engineer -

Technical Engineer

Sr. Golang Developer

Lead Engineer-API/Cloud/DevSecOps Engineer

Principal Engineer - ML Ops

Principal Software Engineer / Lead API developer

Principal Software Engineer / Lead API developer