project engineer

site engineer

planning engineer

technical engineer

it support engineer

ai infrastructure engineer

Google

<div>
 Google welcomes people with disabilities.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 Paris, France; Dubai - United Arab Emirates; Tel Aviv, Israel
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent practical experience.
 </li>
 <li>
 10 years of experience with cloud native architectures and modern cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning, etc.).
 </li>
 <li>
 Experience with high performance infrastructure technology, on-premise infrastructure engineering, virtualization, or containerization platforms and orchestrators such as Slurm, Kubernetes, for building and operationalizing AI Models training and inference.
 </li>
 <li>
 Experience engaging with, and presenting to, technical stakeholders and executive leaders.
 </li>
 <li>
 Experience in networking, switching/routing for ethernet/RoCE/infiniband, in customer-facing or support roles.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Master's degree in Computer Science, Mathematics, or a related technical field.
 </li>
 <li>
 Experience as an IT infrastructure consultant or enterprise architect working in data center investment strategies and proposals.
 </li>
 <li>
 Experience with AI Infrastructure systems, networking technologies (e.g., DPU, RoCE, InfiniBand), cooling, and accelerators, especially GPUs and TPUs.
 </li>
 <li>
 Experience on leveraging main AI hardware and software stacks and platforms to bring up and deploy large-scale AI compute clusters.
 </li>
 <li>
 Knowledge of the AI infrastructure market, including main technology providers, differentiators, and trends.
 </li>
 <li>
 Ability to grow rapidly in an environment, supported by a demonstrated entrepreneurial drive.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
 
 
 As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future using AI technology. You will work with Google Cloud Platform (GCP's) technology and complete AI stack and position the same to our customers in all verticals.
 
 
 As a Customer Engineer, you will support Google Cloud sales teams to incubate, pilot, and deploy Google Cloud&rsquo;s industry leading AI/ML accelerators Tensor Processing Units/Graphical Processing Units (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate faster solutions using Google Cloud&rsquo;s flexible and open AI infrastructure.
 
 
 You will be working with Google customers on AI Infrastructure server and networking infrastructure deployments. In addition, you'll guide customer discussions on network topologies, compute/storage and support to bring up of server/network/cluster/cooling deployments. You will need to visit the customer data center during the bring up phase.
 
 
 Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Understand and incorporate AI accelerators into overall cloud and IT strategy by designing large-scale training and inferencing platforms, using the latest and greatest accelerators Google Cloud has to offer.
 </li>
 <li>
 Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and benchmarking.
 </li>
 <li>
 Work with customers to demonstrate and prototype Google Cloud technology integrations in customer/partner environments, including customer/partner data centers. Help the Account team to close agreements from a technical perspective.
 </li>
 <li>
 Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements, seamlessly collaborating with the AI Infra Dedicated Engineering team.
 </li>
 <li>
 Travel to customer sites, conferences, datacenters, and other related events as needed.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Customer Engineer, Infrastructure Modernization, AI

DICETEK LLC

<div>Description :
Architect Agentic AI Solutions: Design modular systems that integrate LLMs and support multi-step reasoning, retrieval-augmented generation, and tool use.
&sect; AI Model Integration: Select and embed suitable models (e.g., GPT-5, custom LLMs) into scalable platforms.
&sect; Agent Development: Build agents capable of research, summarization, and action execution.
&sect; Infrastructure &amp; Scalability: Use Docker/Kubernetes for containerization and ensure robust monitoring and security.
&sect; Responsible AI Practices: Implement guardrails like content filters, logging, and data protection compliance.
&sect; Customer Collaboration: Translate business needs into technical AI solutions and advise on use cases.
&sect; Continuous Optimization: Analyze agent errors, refine prompts, and improve model performance. 
Skill/Experience/Qualification
Oversee cloud platforms (Azure, AWS) and ensure cost-effective, secure, and compliant operations.
Collaborate with GSO to enforce infrastructure security, identity management, and data protection.
Ensure compliance with regulatory standards (UAE CB | SIA | SAMA)
Champion infrastructure-as-code, CI/CD pipelines, and automation of provisioning and monitoring.
Data Pipeline connectivity &amp; expertise in building optimized, platform-agnostic data pipelines and federated data marts across enterprise. Being able to move data across the sources identified either in a POC or for Production.</div>

Architect Agentic AI Solutions

Talent Connect Group (TCG)

<div>
 
 🚀
 
 Hiring: Lead AI Developer &ndash; UAE
 
 🔥
 
 
 
 
 
 🇮🇳***Relocation from India***
 
 
 
 
 
 Join us at the forefront of
 
 AI innovation in the public sector.
 
 
 
 
 
 
 Our clients are building the foundational AI systems powering the next generation of
 
 intelligent government services
 
 across the UAE.
 
 
 
 
 
 As
 
 Lead AI Developer
 
 , you&rsquo;ll be the technical architect behind our AI infrastructure &mdash; designing, developing, and scaling core machine learning and GenAI platforms
 
 from the ground up
 
 .
 
 
 
 
 
 📍
 
 Location:
 
 Dubai
 
 
 🧠
 
 Focus:
 
 AI Infrastructure for Government Services
 
 
 💰
 
 Salary:
 
 30,000 &ndash; 35,000 AED/month
 
 
 🌍
 
 Impact:
 
 Shape the UAE&rsquo;s AI transformation
 
 
 
 
 
 💼 What You&rsquo;ll Build
 
 <ul>
 <li>
 Architect and implement the
 
 core AI/ML foundations
 
 &mdash; from data pipelines to deployment.
 </li>
 <li>
 Design and deploy
 
 LLMs, diffusion models, and advanced ML algorithms
 
 for real-world applications.
 </li>
 <li>
 Build
 
 end-to-end AI systems
 
 using frameworks like
 
 LangChain, MLflow, Kubeflow, and TensorRT
 
 .
 </li>
 <li>
 Integrate
 
 secure and scalable AI pipelines
 
 for large, sensitive government datasets.
 </li>
 <li>
 Collaborate with product, data science, and security teams to bring
 
 AI prototypes to production
 
 .
 </li>
 </ul>
 
 
 
 
 🧠 What You Bring
 
 <ul>
 <li>
 4&ndash;6+ years of hands-on AI/ML or software engineering experience building products from scratch.
 </li>
 <li>
 Expert in
 
 Python, TensorFlow, PyTorch, and Hugging Face ecosystems.
 
 </li>
 <li>
 Proven experience in
 
 architecting GenAI solutions
 
 and optimizing for cloud (Azure/GCP).
 </li>
 <li>
 Familiarity with
 
 vector DBs, MLOps tools, and containerized microservices (Docker/K8s)
 
 .
 </li>
 <li>
 Strong problem-solving mindset and the ability to
 
 set the technical direction for AI initiatives
 
 .
 </li>
 </ul>
 
 
 
 
 🌟 Nice to Have
 
 <ul>
 <li>
 Experience with
 
 AIOps
 
 ,
 
 open-source projects
 
 , or
 
 UAE public sector deployments.
 
 </li>
 <li>
 Background in scaling AI applications securely in production environments
 </li>
 </ul>
 
 
 
 
 If you are interested please get in touch ASAP with your CV.
 
 
 
 
 
 
 
 
 Owen.Moir-Holland@tconnectgroup.com
 
</div>

Lead AI Developer

PwC Middle East

We are seeking a GenAI Senior Solution Architect to lead the design, development, and deployment of Generative AI-powered applications. This role will focus on architecting scalable AI solutions for cloud-based and hybrid environments, defining AI adoption strategies and best practices, and collaborating with cross-functional teams to drive AI-driven digital transformation. You will play a pivotal role in integrating cutting-edge AI models into enterprise and government systems, ensuring seamless integration into enterprise systems.This role requires expertise in AI architecture, model hosting, MLOps, and full-stack AI application development, with a focus on security, scalability, and performance.Roles And Responsibilities:<ul><li>Architect and implement Generative AI (GenAI) applications cross functionally and across industries such as government, banking, real estate, and telecommunications.</li><li>Define AI adoption strategies and design scalable AI architectures for both cloud-based and hybrid environments.</li><li>Develop AI-driven automation solutions leveraging CoPilot Studio, Power Automate, and other orchestration tools.</li><li>Build and optimize GenAI frameworks using Retrieval-Augmented Generation (RAG), prompt engineering, and LLM integration.</li><li>Deploy offline and cloud-based LLMs using Nvidia Triton, HuggingFace TGI, vLLM, LiteLLM, and other inference layers.</li><li>Lead full-stack AI application development, ensuring high availability, scalability, and security.</li><li>Collaborate with stakeholders to translate business requirements into AI-enabled solutions.</li><li>Implement MLOps best practices, ensuring efficient model training, deployment, and monitoring.</li><li>Manage CI/CD pipelines, containerization (Docker), and DevOps for AI applications.</li><li>Ensure compliance with AI governance, privacy, and security standards in AI Implementations.</li><li>Provide mentorship and technical leadership to AI engineering teams.</li></ul>Required Competencies:<ul><li>Ability to lead cross-country/regional engineering teams.</li><li>Strong business acumen, with the ability to translate business needs into scalable and cost effective AI-enables solutions.</li><li>Experience in AI solution lifecycle management from ideation assessment to production deployment.</li><li>Experience in mitigating AI risks following AI governance, ethics, security and compliance standards.</li><li>Strong problem-solving skills and ability to work in a fast-paced environment.</li></ul>Required Skills:<ul><li>AI expertise: Building RAG models, OpenAI agents, Prompt Engineering, Copilot Studio, Python FastAPI Apps, LangChain, CrewAI</li><li>Proven track record of deploying AI solutions at an enterprise level.</li><li>Ability to build applications and expertise in different technology stacks.</li><li>Expertise in Python, FastAPI, Langchain, Langfuse, LlamaIndex.</li><li>Strong experience with AI model hosting, fine-tuning, and API integration.</li><li>Hands-on experience with Cloud Platforms (Azure, AWS, GCP) for AI/ML workloads.</li><li>Proficiency in MLOps, AI Infrastructure Engineering, and Data Engineering.</li><li>Experience in containerization, CI/CD pipelines, and DevOps practices.</li><li>Deep knowledge in LLM architecture, RAG, and inference optimization.</li><li>Knowledge of data privacy, security and ethical AI governance frameworks.</li><li>Understanding of AI governance frameworks and best practices for ethical AI.</li><li>Experience with full-stack development for AI applications if preferable.</li><li>Strong problem-solving skills and ability to work in a fast-paced environment.</li><li>Experience working with government entities and large enterprises is a plus.</li></ul>

GenAI Solution Architect

PricewaterhouseCoopers

Job Summary: We value every individual's role in shaping our future. We're looking for candidates who excel in their roles and embody our core behaviors of Trusted Leadership and Distinctive Outcomes. Trusted Leadership focuses on building trust, delivering sustained results, and showing courage and honesty. Distinctive Outcomes emphasize excellence, collaboration, and inclusiveness. We seek self-aware, collaborative individuals committed to continuous learning and delivering quality and integrity. We are seeking a GenAI Senior Solution Architect to lead the design, development, and deployment of Generative AI-powered applications. This role will focus on architecting scalable AI solutions for cloud-based and hybrid environments, defining AI adoption strategies and best practices, and collaborating with cross-functional teams to drive AI-driven digital transformation. You will play a pivotal role in integrating cutting-edge AI models into enterprise and government systems, ensuring seamless integration into enterprise systems. This role requires expertise in AI architecture, model hosting, MLOps, and full-stack AI application development, with a focus on security, scalability, and performance. Roles and Responsibilities: <ul> <li>Architect and implement Generative AI (GenAI) applications cross functionally and across industries such as government, banking, real estate, and telecommunications.</li> <li>Define AI adoption strategies and design scalable AI architectures for both cloud-based and hybrid environments.</li> <li>Develop AI-driven automation solutions leveraging CoPilot Studio, Power Automate, and other orchestration tools.</li> <li>Build and optimize GenAI frameworks using Retrieval-Augmented Generation (RAG), prompt engineering, and LLM integration.</li> <li>Deploy offline and cloud-based LLMs using Nvidia Triton, HuggingFace TGI, vLLM, LiteLLM, and other inference layers.</li> <li>Lead full-stack AI application development, ensuring high availability, scalability, and security.</li> <li>Collaborate with stakeholders to translate business requirements into AI-enabled solutions.</li> <li>Implement MLOps best practices, ensuring efficient model training, deployment, and monitoring.</li> <li>Manage CI/CD pipelines, containerization (Docker), and DevOps for AI applications.</li> <li>Ensure compliance with AI governance, privacy, and security standards in AI Implementations.</li> <li>Provide mentorship and technical leadership to AI engineering teams.</li> </ul> Required Skills: <ul> <li>AI expertise: Building RAG models, OpenAI agents, Prompt Engineering, Copilot Studio, Python FastAPI Apps, LangChain, CrewAI</li> <li>Proven track record of deploying AI solutions at an enterprise level.</li> <li>Ability to build applications and expertise in different technology stacks.</li> <li>Expertise in Python, FastAPI, Langchain, Langfuse, LlamaIndex.</li> <li>Strong experience with AI model hosting, fine-tuning, and API integration.</li> <li>Hands-on experience with Cloud Platforms (Azure, AWS, GCP) for AI/ML workloads.</li> <li>Proficiency in MLOps, AI Infrastructure Engineering, and Data Engineering.</li> <li>Experience in containerization, CI/CD pipelines, and DevOps practices.</li> <li>Deep knowledge in LLM architecture, RAG, and inference optimization.</li> <li>Knowledge of data privacy, security and ethical AI governance frameworks.</li> <li>Understanding of AI governance frameworks and best practices for ethical AI.</li> <li>Experience with full-stack development for AI applications if preferable.</li> <li>Strong problem-solving skills and ability to work in a fast-paced environment.</li> <li>Experience working with government entities and large enterprises is a plus.</li> </ul> Required Language Skills: <ul> <li>Fluent English</li> <li>Arabic proficiency is a plus</li> </ul>

Glow Beauty On Demand

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer Generative AI & Machine Learning Infrastructure

Explore 2810+ Ai infrastructure engineer in Dubai this November. Find roles across top companies and apply now to boost your career.

2810 ai infrastructure engineer jobs IN Dubai

Customer Engineer, Infrastructure Modernization, AI

Architect Agentic AI Solutions

Lead AI Developer

GenAI Solution Architect

GenAI Solution Architect

ML Platform Engineer

ML Platform Engineer Generative AI & Machine Learning Infrastructure