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ai inference infrastructure engineer

Dizzaract FZ LLC

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.The Mission: We are building a highly optimized, decentralized AI inference network. To beat the latency and throughput of established centralized players, we cannot rely on off-the-shelf wrappers. You will be responsible for building the bare-metal, ultra-low-latency infrastructure that serves large language models and multimodal networks at unprecedented scale.What You Will Do:<ul><li>Core Engine Development: Architect and write highly optimized, low-level code (primarily in Rust and C) to manage model loading, memory allocation, and request batching across a distributed fleet of GPUs/NPUs.</li><li>Hardware-Aware Optimization: Implement tensor mathematics optimizations and custom kernels (CUDA/Triton) to squeeze maximum FLOPS out of the hardware.</li><li>Zero-Intervention Deployments: Build rock-solid, fully packaged infrastructure pipelines. We operate with zero manual intervention&mdash;no ad-hoc scripts, no PowerShell bandaids. If a node fails, the network must heal autonomously.</li><li>Decentralized Orchestration: Design the peer-to-peer or decentralized routing logic that ensures high availability and optimal load balancing across geographically distributed nodes.</li><li>Advanced Inference Techniques: Implement and optimize techniques like continuous batching, speculative decoding, and paged attention (vLLM, TensorRT-LLM) customized for our specific network architecture.</li></ul>What We Are Looking For:<ul><li>Deep expertise in systems programming (Go) and a strong aversion to bloated, high-level abstractions where performance matters.</li><li>Proven experience with GPU programming (CUDA, ROCm) and low-level hardware architecture.</li><li>Strong understanding of deep learning architectures (Transformers, Mamba) and how tensor operations execute on silicon.</li><li>Experience building highly concurrent, distributed systems with sub-millisecond network latency requirements.</li></ul>Work Location: In person

AI Inference Infrastructure Engineer

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.Role SummaryWe are seeking a strategic Business Developer with deep expertise in AI models, inference, and MLOps commercialization. You will be responsible for identifying, negotiating, and closing B2B partnerships to monetize our proprietary AI models and inference capabilities. This role sits at the intersection of technology and business &mdash; you will translate complex AI technical value (latency, throughput, model accuracy, cost per inference) into revenue-generating opportunities.Key Responsibilities1. AI Business Development &amp; Partnerships<ul><li>Identify and secure partnerships with enterprises, developers, and platforms needing AI inference solutions (LLMs, computer vision, generative AI for gaming).</li><li>Build a go-to-market strategy for FAR Labs&rsquo; proprietary AI models and inference infrastructure.</li><li>Develop licensing models: API calls, subscription tiers, on-prem inference, or revenue-share agreements.</li><li>Lead the full sales cycle: lead generation, technical scoping, proposal writing, contract negotiation, and closing.</li></ul>2. Monetization of Inference &amp; Model APIs<ul><li>Collaborate with engineering to define pricing strategies based on inference cost (compute, tokens, latency, batch size).</li><li>Package our R&amp;D output (20+ patents, 100+ papers) into sellable AI products: game AI agents, player behavior models, identity verification AI (GAMED).</li><li>Create technical marketing materials: case studies, inference benchmarks, model cards, and demos.</li></ul>3. Market &amp; Competitive Intelligence<ul><li>Track the AI inference landscape: cloud providers (AWS Bedrock, Azure AI, Replicate), open-source models, and emerging competitors.</li><li>Identify gaps where Dizzaract&rsquo;s models outperform in latency, cost, or domain-specific tasks (competitive gaming, real-time AI).</li><li>Provide feedback to R&amp;D on market needs (model size, quantization, edge inference requirements).</li></ul>4. Customer &amp; Technical Engagement<ul><li>Serve as the bridge between external clients and our ML engineering team &mdash; translate business needs into technical requirements (batch vs real-time inference, GPU/CPU tradeoffs, SLAs).</li><li>Support clients with POCs, integration of our inference APIs, and performance validation.</li><li>Collect and prioritize feature requests for our inference stack (scaling, observability, versioning).</li></ul>5. Strategic Growth &amp; OKRs<ul><li>Define and track BD KPIs: number of active partnerships, monthly recurring inference revenue (MRR), customer acquisition cost (CAC), and gross margin per inference.</li><li>Implement a quarterly OKR framework for the BD team aligned with company revenue goals.</li><li>Report directly to COO and the Director of BD on pipeline, forecasts, and strategic deals.</li></ul>Required Qualifications &amp; Skills<ul><li>3+ years in business development, partnerships, or technical sales focused on AI/ML models or inference platforms.</li><li>Strong understanding of inference concepts: model serving, batching, latency vs throughput, token-based pricing, fine-tuning, and quantization.</li><li>Ability to read basic API docs and discuss model performance with engineers (no need to code, but technical fluency is a must).</li><li>Proven track record of closing B2B SaaS or API-based deals, preferably with gaming, media, or security clients.</li><li>Familiarity with AI deployment tools (Hugging Face, TensorRT, vLLM, or cloud inference endpoints) is a strong plus.</li><li>Excellent negotiation, communication, and presentation skills for technical and non-technical audiences.</li><li>Self-starter mindset, comfortable with remote work and fast-paced R&amp;D environments.</li></ul>Final NoteThis role is for a business-savvy AI expert who wants to turn cutting-edge research into real revenue. You will have direct access to 20+ patents, a world-class R&amp;D team, and an emerging AI ecosystem in Abu Dhabi. If you understand inference pricing models, can sell APIs to developers and enterprises, and want to shape the commercial future of AI in gaming &mdash; this is your opportunity.Work Location: In person

Business Developer Executive

YO IT Consulting

<div>
 
 Job Title:
 
 AI/ML Engineer
 
 
 
 Job Type:
 
 Full-Time
 
 
 
 Job Summary
 
 
 
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
 </li>
 <li>
 Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
 </li>
 <li>
 Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
 </li>
 <li>
 Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
 </li>
 <li>
 Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
 </li>
 <li>
 Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
 </li>
 <li>
 Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
 </li>
 <li>
 Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
 </li>
 <li>
 Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
 </li>
 <li>
 Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
 </li>
 <li>
 Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
 </li>
 <li>
 Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
 </li>
 <li>
 Exceptional written and verbal communication skills for effective collaboration and documentation.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
 </li>
 <li>
 Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
 </li>
 <li>
 Prior exposure to government or highly regulated cloud environments and compliance standards.
 </li>
 </ul>
</div>

AI/ML Engineer - Remote

Inception

<div>
 Inception, a G42 company, is the region&rsquo;s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer &ndash; transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inceptionai.ai
 
 
 
 Overview
 
 
 
 Inception is seeking a highly skilled Lead Data Engineer to architect and build scalable, cloud-native data and AI pipelines that power enterprise LLM, RAG, and retrieval systems.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and optimize scalable data pipelines for AI/LLM workloads, including vectorization and embedding processing.
 </li>
 <li>
 Develop and maintain ETL/ELT workflows for structured, unstructured, and streaming data.
 </li>
 <li>
 Create and manage vector database indexing and similarity search pipelines using tools like FAISS, Pinecone, Weaviate, Qdrant, Chroma.
 </li>
 <li>
 Build retrieval systems for RAG, semantic search, and enterprise knowledge retrieval.
 </li>
 <li>
 Develop robust, reusable data orchestration pipelines using Airflow, Spark, or similar tools.
 </li>
 <li>
 Architect and manage data pipelines across Azure (primary), AWS, and GCP environments.
 </li>
 <li>
 Integrate and optimize storage and processing across SQL, NoSQL, and vector databases.
 </li>
 <li>
 Contribute to the design and implementation of event-driven architectures.
 </li>
 <li>
 Collaborate with AI teams to enable embedding generation, LLM integration, and model-serving pipelines.
 </li>
 <li>
 Ensure end-to-end data quality, monitoring, reliability, and observability.
 </li>
 <li>
 Lead or participate in system design for large-scale, distributed data and AI systems.
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 
 Programming &amp; Data
 
 
 
 <ul>
 <li>
 Strong expertise in Python for data processing, APIs, automation, or distributed workloads.
 </li>
 <li>
 Strong proficiency in SQL and knowledge of NoSQL databases (MongoDB, DynamoDB, Cosmos DB, etc.).
 </li>
 <li>
 Experience with vector databases, such as: FAISS, Pinecone, Weaviate, Qdrant, Chroma.
 </li>
 <li>
 Strong knowledge of data modeling, pipeline development, and ETL/ELT frameworks.
 
 
 </li>
 </ul>
 
 AI/LLM Infrastructure
 
 
 
 <ul>
 <li>
 Solid understanding of vectorization, embeddings, and similarity search techniques.
 </li>
 <li>
 Familiarity with LLMs, embedding models, and RAG pipeline concepts.
 </li>
 <li>
 Experience integrating embedding-generation pipelines via Hugging Face, OpenAI, or other model providers.
 
 
 </li>
 </ul>
 
 Cloud &amp; Distributed Systems
 
 
 
 <ul>
 <li>
 Proficiency with Azure (primary), and familiarity with AWS and GCP.
 </li>
 <li>
 Experience with Docker and containerized development.
 </li>
 <li>
 Understanding of Kubernetes is a strong plus.
 
 
 </li>
 </ul>
 
 Orchestration &amp; Big Data
 
 
 
 <ul>
 <li>
 Expertise in Apache Airflow for scheduling and orchestration.
 </li>
 <li>
 Experience with Apache Spark or equivalent distributed processing frameworks.
 
 
 </li>
 </ul>
 
 Architecture &amp; Engineering Fundamentals
 
 
 
 <ul>
 <li>
 Strong system design fundamentals for scalable and distributed systems.
 </li>
 <li>
 Knowledge of event-driven architecture and modern data platforms.
 </li>
 <li>
 Strong understanding of DevOps, CI/CD, version control, and observability best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 8+ years of progressive experience in data engineering, distributed systems, or AI/ML data infrastructure
 </li>
 <li>
 Experience building RAG pipelines in production.
 </li>
 <li>
 Knowledge of graph databases or hybrid search systems.
 </li>
 <li>
 Understanding of model deployment, inference optimization, and caching techniques for LLM workloads.
 </li>
 <li>
 Familiarity with data governance, IAM, and security patterns across cloud ecosystems
 
 
 </li>
 </ul>
 What We Look For
 
 
 If you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception community.
 
 
 What Working At Inception Offers
 
 
 Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.
 
 
 Career: Outstanding learning, development &amp; growth opportunities via structured training programs and innovative, high-tech projects.
 
 
 Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.
 
 
 If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.
</div>

Lead Data Engineer

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.The Mission: An inference network routing millions of requests globally generates a massive, complex data exhaust. You will build the data plane that fuels our routing intelligence, telemetry, and distributed memory systems. To beat OpenRouter, our network needs to route requests intelligently based on real-time hardware metrics and cost analysis without adding latency.What You Will Do:<ul><li>High-Throughput Telemetry: Design pipelines to ingest, process, and analyze millions of telemetry events per second (GPU utilization, TTFT, inter-token latency) from distributed nodes.</li><li>Distributed KV-Cache Architecture: Architect the data layer for distributed KV-cache storage and retrieval, allowing the network to context-switch efficiently across different compute nodes.</li><li>Intelligent Routing State: Build the real-time data stores that power our routing layer, ensuring the network always knows the exact state, cost, and availability of every node globally.</li><li>Ledger &amp; Analytics: Develop the backend pipelines for billing, rate-limiting, and auditing, ensuring airtight data consistency for high-frequency micro-transactions.</li><li>Data Packaging: Ensure all data infrastructure deployments are containerized, immutable, and require zero manual configuration upon deployment.</li></ul>What We Are Looking For:<ul><li>Expertise in high-throughput messaging and streaming systems (e.g., Redpanda, Kafka) and real-time OLAP databases (e.g., ClickHouse).</li><li>Strong proficiency in backend languages (Rust, Go, or Python) with a focus on high concurrency and low latency.</li><li>Experience with vector databases and managing massive, distributed state.</li><li>A strong grasp of distributed consensus algorithms and data replication across decentralized environments.</li></ul>Work Location: In person

AI Inference Data Engineer

RE/MAX Smart Concept

Job description:Job description:Job Title: AI Automation Engineer - Real Estate Experience Location: Abu Dhabi, UAE Job Type: Full-Time | Office-Based Company: RE/MAX Smart Concept Real EstateAbout the PositionRE/MAX Smart Concept Real Estate is seeking a highly capable AI Automation Engineer to build and maintain automation workflows across our CRM and internal operational systems.This role is hands-on and execution focused, responsible for developing reliable automation systems, implementing API integrations, and ensuring long-term system stability.We are looking for a professional who can design and manage automation infrastructure that operates consistently, efficiently, and without disruption.Real Estate Industry Experience &ndash; Highly PreferredCandidates with experience working within real estate technology environments will be given priority, especially those familiar with:<ul><li>Real estate brokerage systems</li><li>Property management platforms</li><li>CRM environments used in real estate companies</li><li>Lead routing and distribution systems</li><li>Property listing integrations</li><li>Portal connectivity and data synchronization</li></ul>Understanding agent workflows, listing distribution, and real estate lead management will be considered a strong advantage.Key Responsibilities<ul><li>Design and implement automation workflows using Make, Zapier, or n8n</li><li>Integrate CRM systems using API-based read and write operations</li><li>Connect automation workflows with platforms such as:</li><li>Slack</li><li>Email systems</li><li>WhatsApp Business API</li><li>Implement structured logging, monitoring, retry mechanisms, and error handling</li><li>Test, document, and maintain automation systems</li><li>Ensure reliability, performance, and long-term operational stability</li><li>Maintain ownership of automation infrastructure and integrations</li></ul>Required Qualifications<ul><li>Strong hands-on experience with Make, Zapier, or n8n</li><li>Proven experience integrating CRM platforms through APIs (Bitrix24 or similar systems preferred)</li><li>Experience integrating Slack, Email services, and WhatsApp Business API</li><li>Solid understanding of:</li><li>REST APIs</li><li>Webhooks</li><li>Automation logic (Trigger &rarr; Action)</li><li>Data flow architecture</li><li>Error handling and retry strategies</li></ul>Important Notes<ul><li>This role focuses strictly on automation engineering and system execution</li><li>The position does not involve AI model training or LLM research</li><li>No responsibilities related to CRM redesign or consulting</li><li>Long-term ownership of automation systems is expected</li><li>We are looking for candidates with production-level experience and a strong focus on system reliability</li></ul>Employment DetailsEmployment Type: Full-Time Location: Abu Dhabi, UAE (Office-Based) Department: Technology / SystemsThis position offers long-term responsibility for automation infrastructure within a growing real estate organization.Application ProcessInterested candidates should submit their CV along with a short summary including:<ul><li>Examples of automation systems built in production</li><li>CRM platforms integrated</li><li>Tools and technologies used</li><li>Experience working with real estate companies (if applicable)</li></ul>Job Type: Full-timeExperience:<ul><li>Real Estate : 1 year (Required)</li></ul>Work Location: In person

AI Automation

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 Engineer
 
 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 designing, developing, and maintaining scalable data pipelines that support analytics, reporting, and AI/ML initiatives for data center operations. The Data Engineer will ensure data integrity, optimize data architecture, and manage ETL (Extract, Transform, Load) processes across cloud and on-premises platforms to enable effective, data-driven decision-making.
 
 
 
 
 
 
 Key Accountabilities:
 
 
 
 
 
 <ul>
 <li>
 Support the development of scalable data warehouses, lakes and resilient data pipelines to support high-velocity data processing in a wholesale data center environment
 </li>
 <li>
 Design and implement Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to clean, normalize and transform data from diverse sources, including Internet of Things (IoT) sensors, Building Management System (BMS) within data center operations
 </li>
 <li>
 Automate data ingestion, transformation and storage workflows for real-time analytics, ensuring low-latency insights for operational decision-making across data center environments
 </li>
 <li>
 Set up streaming data services to enable continuous migration of critical data center infrastructure metrics into analytics platforms for real-time monitoring
 </li>
 <li>
 Work with Integration teams, Data Warehouse engineers and Analytics teams to build highly optimized, resilient and scalable data center data processing architectures
 </li>
 <li>
 Define data sourcing strategies, tagging mechanisms and aggregation methods to ensure seamless availability of structured and unstructured data for data center analytics
 </li>
 <li>
 Collaborate with Data Scientists and Business Intelligence (BI) teams to enable AI/ML model development, predictive analytics and operational intelligence for data center operations
 </li>
 <li>
 Develop calculation methodologies for statistical computation of KPIs related to Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), uptime and asset utilization in data centers
 </li>
 <li>
 Identify critical data points and sources that drive KPI computations and aggregate site-level metrics for centralized data center performance reporting
 </li>
 <li>
 Build reporting source files for dashboards, enabling executive leadership to monitor data center performance trends across regional and site-level operations
 </li>
 <li>
 Generate historical trend analyses, benchmarking individual data center site performance against portfolio-wide averages to drive efficiency improvements
 </li>
 <li>
 Conduct Exploratory Data Analysis (EDA) to identify patterns, anomalies and correlations that impact energy efficiency, workload distribution and infrastructure health in data centers
 </li>
 <li>
 Gather required historical and real-time data from internal platforms and external sources, ensuring comprehensive datasets for advanced analytics in data center environments
 </li>
 <li>
 Develop simulations and scenario models to analyse potential business impacts, optimize data center capacity planning and mitigate operational risks
 </li>
 <li>
 Update models and forecasting frameworks based on market trends, data center infrastructure expansion plans and internal priority shifts
 </li>
 <li>
 Research and implement cutting-edge data engineering techniques, contributing to industry-leading best practices in large-scale data center data infrastructure management
 </li>
 <li>
 Deliver data archiving, backup and disaster recovery strategies, ensuring high availability and business continuity for critical data center data assets
 </li>
 <li>
 Ensure seamless integration of data platforms with enterprise applications, enabling end-to-end visibility and automated decision-making across the data center ecosystem
 </li>
 </ul>
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science (or) related to Data Engineering
 </li>
 <li>
 Certifications in cloud data platforms preferred
 </li>
 <li>
 4+ years of experience in data engineering, ETL development or database management
 </li>
 <li>
 Strong proficiency in SQL, Python or Scala
 </li>
 <li>
 Experience with cloud data platforms (AWS, Azure, GCP)
 </li>
 <li>
 Hands-on experience with data pipeline tools like Apache Airflow, Kafka or Spark
 </li>
 <li>
 Understanding of data modeling, warehousing and governance principles
 </li>
 </ul>
 
 
 
 
 
 Additional skills:
 
 
 
 
 
 <ul>
 <li>
 Ability to troubleshoot complex data challenges, optimize pipeline performance and drive continuous improvements in large-scale infrastructure
 </li>
 <li>
 Strong ability to work across Data Science, Engineering, IT and Business Intelligence teams to align data solutions with business needs
 </li>
 <li>
 Expertise in translating technical data models and engineering concepts into clear insights for non-technical stakeholders
 </li>
 </ul>
 
 
 
 
 
 Training/Certifications Preferred:
 
 
 
 
 
 <ul>
 <li>
 AWS Certified Data Analytics &ndash; Specialty
 </li>
 <li>
 Google Professional Data Engineer
 </li>
 <li>
 Microsoft Certified: Azure Data Engineer Associate
 </li>
 <li>
 Apache Spark Developer Certification
 </li>
 </ul>
 
 
</div>

Data Engineer

Explore 510+ Ai inference infrastructure engineer in Abu Dhabi this April. Find roles across top companies and apply now to boost your career.