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HUED | هيود

<div>
 
 
 Job Summary
 
 
 
 We are seeking an experienced AI Applications / Solutions Engineer to design, build, and deploy intelligent solutions powered by modern AI technologies. The ideal candidate will have strong expertise in Large Language Models (LLMs), Generative AI (GenAI), and Retrieval-Augmented Generation (RAG) systems, with the ability to integrate AI models with enterprise data and business workflows.
 
 
 This role requires a strong software engineering background combined with hands-on experience in developing scalable AI-driven applications, optimizing model performance, and delivering production-ready solutions.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI technologies.
 </li>
 <li>
 Build and optimize Retrieval-Augmented Generation (RAG) pipelines integrated with enterprise data sources.
 </li>
 <li>
 Develop effective prompt engineering strategies to improve AI output quality, consistency, and reliability.
 </li>
 <li>
 Prepare and process structured and unstructured datasets for AI model consumption, including data cleaning, chunking, and embedding generation.
 </li>
 <li>
 Integrate AI systems with internal platforms, APIs, and business applications.
 </li>
 <li>
 Work with vector databases such as Pinecone or FAISS for semantic search and knowledge retrieval.
 </li>
 <li>
 Evaluate model performance and continuously improve solution accuracy, latency, and scalability.
 </li>
 <li>
 Collaborate with cross-functional teams to identify AI use cases and deliver business-driven solutions.
 </li>
 <li>
 Stay updated with the latest advancements in AI, LLMs, and GenAI technologies.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, Software Engineering, AI, or a related field.
 </li>
 <li>
 Minimum 4 years of software development experience.
 </li>
 <li>
 Recent hands-on experience in Artificial Intelligence, particularly in LLM and GenAI applications.
 </li>
 <li>
 Strong understanding of Large Language Models (LLMs) and their practical applications.
 </li>
 <li>
 Proven experience in designing and implementing Generative AI solutions.
 </li>
 <li>
 Strong experience in Prompt Engineering.
 </li>
 <li>
 Hands-on experience building RAG solutions.
 </li>
 <li>
 Strong proficiency in Python.
 </li>
 <li>
 Experience in data preparation for AI systems (Cleaning, Chunking, Embedding).
 </li>
 <li>
 Experience working with vector databases such as Pinecone or FAISS.
 </li>
 <li>
 Familiarity with Fine-Tuning techniques is a strong plus.
 </li>
 </ul>
</div>

Artificial Intelligence Engineer

Unified Real Estate Development Company

<div>
 
 
 Core Responsibilities:
 
 
 <ul>
 <li>
 Design and build the central data infrastructure (ClickHouse, data lake, or equivalent) that aggregates data from property management, leasing, finance, and operations systems.
 </li>
 <li>
 Integrate frontier LLMs (Claude, GPT-4, or equivalent) via API to serve as the reasoning and analysis layer on top of internal data.
 </li>
 <li>
 Build and maintain retrieval pipelines that intelligently select, filter, and deliver relevant data to the LLM within context window constraints.
 </li>
 <li>
 Develop internal tools, dashboards, or interfaces that allow non-technical staff to interact with AI-powered analysis.
 </li>
 <li>
 Implement proper data security, access controls, and compliance protocols &mdash; ensuring sensitive real estate and tenant data is handled appropriately.
 </li>
 <li>
 Architect systems with modularity in mind &mdash; LLM providers, data sources, and tools should be swappable as the landscape evolves.
 </li>
 <li>
 Monitor AI output quality and implement validation/feedback loops to catch hallucinations and errors.
 </li>
 <li>
 Stay current with AI developments and proactively recommend when new capabilities become relevant to Unified&rsquo;s operations.
 </li>
 <li>
 Document all systems, architectures, and processes thoroughly. Bus-factor risk must be minimized.
 </li>
 </ul>
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 3&ndash;5 years of software engineering experience, with strong proficiency in Python.
 </li>
 <li>
 Hands-on experience building applications that integrate with LLM APIs (Anthropic, OpenAI, or similar).
 </li>
 <li>
 Practical knowledge of data engineering: ETL pipelines, SQL, working with structured and semi-structured data on scale.
 </li>
 <li>
 Experience with at least one of: ClickHouse, PostgreSQL, BigQuery, Snowflake, or comparable analytical databases.
 </li>
 <li>
 Understanding of retrieval-augmented generation (RAG) patterns, vector databases, and context management strategies.
 </li>
 <li>
 Familiarity with orchestration frameworks (LangChain, LlamaIndex, or custom equivalents).
 </li>
 <li>
 Ability to deploy and maintain production services (Docker, cloud infrastructure, CI/CD basics).
 </li>
 <li>
 Strong communication skills &mdash; you will need to explain technical constraints and trade-offs to non-technical stakeholders clearly.
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Experience in real estate, property management, or construction technology is a strong plus but not required.
 </li>
 <li>
 Exposure to agent-based AI workflows and multi-step task orchestration.
 </li>
 <li>
 Experience with data visualization tools or building internal dashboards (Streamlit, Retool, or custom).
 </li>
 <li>
 Familiarity with Arabic language NLP or bilingual data environments.
 </li>
 <li>
 Previous experience working in small teams or startup-like environments where you owned projects end-to-end.
 </li>
 </ul>
 
 
 What This Role Is Not
 
 
 <ul>
 <li>
 This is not an ML research role. You will not be training or fine-tuning models. You will be implementing and integrating existing frontier models.
 </li>
 <li>
 This is not a pure data engineering role. You will build data infrastructure, but the goal is to power AI applications, not just maintain databases.
 </li>
 <li>
 This is not a management role. This is an individual contributor position with high autonomy and direct impact.
 </li>
 </ul>
 
 
 Working Arrangement
 
 
 
 Based in Riyadh. You will participate in weekly rotating meetings with different departments (leasing, property management, finance, operations) alongside the AI Analyst to understand business needs and demonstrate progress. Expect a fast iteration cycle &mdash; the expectation is working prototypes, not lengthy planning phases.
 
</div>

SiFi

<div>
 
 
 About Us
 
 
 
 
 SiFi is building the next-generation Office of the CFO &mdash; a corporate expense management platform that gives accounting teams seamless control over company spending. We let companies issue cards with precise spending restrictions, automate expense workflows, and close books faster. As we scale, AI is becoming core to how we deliver financial intelligence, automation, and trust to our customers.
 
 
 
 We are a small, high-ownership team. Everyone builds, everyone ships, and everyone is accountable for outcomes.
 
 
 
 
 About the Role
 
 
 
 
 We are looking for an AI Engineer to join our Data &amp; AI team and help us bring AI-powered automation into the heart of corporate finance. You will work across the full stack &mdash; from LLM pipelines and agent workflows to the backend infrastructure and internal tooling that makes them production-ready.
 
 
 
 This is a hands-on, end-to-end role. You will own problems from prototype to production &mdash; in a domain where financial data is structured, high-stakes, and unforgiving. Getting it wrong has real consequences for real companies. You will work closely with Product, Engineering, Finance, and Operations to build AI features that make a direct impact on how hundreds of companies manage money.
 
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design and ship AI-powered features end to end &mdash; from prompt engineering and model integration to backend APIs and frontend surfaces.
 
 </li>
 <li>
 Build and maintain AI infrastructure for LLM inference, retrieval-augmented generation (RAG), and structured data extraction from financial documents
 
 </li>
 <li>
 Develop autonomous agent workflows that automate finance operations such as expense categorization, receipt reconciliation, and policy enforcement
 
 </li>
 <li>
 Partner with the Data Engineering team to ensure AI systems are grounded in clean, trusted, and well-modeled financial data.
 
 </li>
 <li>
 Build internal tooling and evaluation frameworks to measure, monitor, and improve model performance in production.
 
 </li>
 <li>
 Stay close to the state of the art and bring relevant techniques &mdash; fine-tuning, tool use, multi-agent orchestration &mdash; into SiFi's stack where they create real value
 
 
 
 </li>
 </ul>
 Requirements
 
 
 - Strong engineering fundamentals across backend systems, APIs, and cloud infrastructure &mdash; you are comfortable owning the full lifecycle of a production AI feature.
 
 
 - Hands-on experience building with LLMs in production, including prompt design, RAG pipelines, structured extraction, or Agentic systems
 
 
 - Comfort working with financial or compliance-sensitive data, where correctness and audit ability matter
 
 
 - A bias toward shipping &mdash; you move fast, make pragmatic trade offs, and iterate based on real-world feedback
 
 
 - Low ego, high ownership: you are as comfortable debugging an edge case as you are proposing a new system architecture
 
 
 
 
 Nice to Have
 
 
 
 
 - Familiarity with fin-tech or expense management domains
 
 
 - Prior work at an early-stage startup or in a small, high-velocity team
 
 
 
 
 Benefits
 
 
 
 
 Why SiFi
 
 
 
 <ul>
 <li>
 Work on AI problems that are genuinely hard: financial data is structured, high-stakes, and unforgiving &mdash; the opposite of toy problems
 
 </li>
 <li>
 Own meaningful surface area from day one on a lean team where your decisions shape the product.
 
 </li>
 <li>
 Competitive salary and equity
 
 </li>
 <li>
 Flexible working environment
 
 </li>
 <li>
 A front-row seat to building a category-defining fin-tech from the ground up
 
 </li>
 </ul>
</div>

AI Engineer

MASTER-WORKS

<div>Our subsidiary (Nabeh) is seeking an AI Solution, Engineer who combines strong technical knowledge in AI and software engineering with excellent customer-facing and presentation skills. The role will work closely with Sales, Product, and Engineering teams to understand customer requirements, define solution scope, build Proofs of Concept, demonstrate AI products, and translate business needs into practical technical solutions.
Key Responsibilities:<ul><li>
Build and deliver AI Proofs of Concept and technical prototypes.</li><li>
Support Sales during customer meetings, workshops, and product demonstrations.</li><li>
Understand customer requirements and translate them into clear technical and product scopes.</li><li>
Evaluate AI models and technologies based on accuracy, performance, and business needs.</li><li>
Prepare high-level solution architectures, workflows, and technical documentation.</li><li>
Support technical proposals, RFPs, and RFIs.</li><li>
Define POC success criteria, assumptions, limitations, and dependencies.</li><li>
Coordinate with Product and Engineering teams to ensure smooth project handover.</li><li>
Collect customer feedback and recommend product enhancements.</li><li>
Communicate technical capabilities and limitations to technical and non-technical stakeholders.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.</li><li>
+3 years of experience in AI engineering, software engineering, solution engineering, or technical pre-sales.</li><li>
Strong knowledge of AI, machine learning, Generative AI, and software development.</li><li>
Hands-on experience with Python, APIs, databases, and backend development.</li><li>
Familiarity with LLMs, RAG, computer vision, speech AI, or document intelligence.</li><li>
Ability to build prototypes and integrate AI models into applications.</li><li>
Strong communication, presentation, and problem-solving skills.</li><li>
Ability to translate business requirements into practical technical solutions.</li><li>
Native Arabic speaker is mandatory.</li><li>
Strong professional proficiency in English is required.</li></ul>
Preferred Skills<ul><li>
FastAPI, Flask, or Django</li><li>
PostgreSQL and vector databases</li><li>
Docker and Kubernetes</li><li>
Cloud and on-premises AI deployments</li><li>
AI model serving and GPU infrastructure</li><li>
Product demonstrations and technical proposal writing</li></ul>
Job location: HQ</div>

AI Solution, Engineer

COGNNA

<div>As a Threat Detection Engineer at COGNNA, you&rsquo;ll design high-impact detection strategies, build powerful automation, and elevate SOC operations to a world-class standard. You&rsquo;ll also mentor rising cyber talent and collaborate with teams across threat intel, incident response, and platform engineering. 
 
Advanced Threat Detection Engineering<ul><li>
Build high-fidelity correlation rules and behavioral detections within the COGNNA security platforms.</li><li>
Translate adversary TTPs (MITRE ATT&amp;CK), threat intel, and vulnerability data into actionable logic.</li><li>
Identify detection gaps and introduce new data sources to cover evolving threat landscapes.</li><li>
Automate detection testing and maintain detection quality over time.</li></ul><ul><li>️ Platform Engineering &amp; Optimization</li></ul><ul><li>
Lead architecture and optimization of XDR, SIEM, and SOC tech stacks for scale and resilience.</li><li>
Streamline log ingestion pipelines &mdash; from parsing to normalization and enrichment.</li><li>
Build scripts and automations (Python, PowerShell) to enhance SOC efficiency.</li>
Integrate tools across the SOC stack to enable seamless workflows and response. 
<li>
</li></ul>️&zwj;️ Threat Hunting &amp; Incident Response<ul><li>
Collaborate with intel and IR teams to enrich detection use cases and support threat hunts.</li><li>
Provide Tier-3+ support for incident investigations and post-mortem analysis.</li></ul>
Mentorship &amp; SOC Maturity<ul><li>
Improve SOC playbooks, SOPs, and detection engineering workflows.</li><li>
Stay updated on global and regional threats &mdash; and evolve detection accordingly.</li><li>
Ensure compliance alignment (e.g., NCA ECC, SAMA CSF).</li></ul> 

Requirements 

Education<ul><li>
Bachelor&rsquo;s in Computer Science, Cybersecurity, or related field. 
</li></ul>Experience<ul><li>
Hands-on expertise in developing and maintaining complex detection use cases.</li><li>
Strong understanding of attacker behavior, IR fundamentals, and digital forensics. 
</li></ul>Technical Skills (You&rsquo;re a Power User!)<ul><li>
SIEM: Expert in SIEM queries (SPL, KQL, Lucene), rule tuning, UEBA, and scaling.</li><li>
EDR: Deep knowledge of EDR tools and endpoint detection tactics.</li><li>
Network Security: Pro at packet analysis (Wireshark), IDS/IPS, and NetFlow.</li><li>
Scripting: Advanced skills in Python and/or PowerShell for automation and integration.</li><li>
OS Internals: Mastery of Windows/Linux/macOS logging, artifacts, and forensic value.</li><li>
Threat Intelligence: Skilled in turning threat intel into real-time detection logic.</li><li>
Cloud Security: Strong command of monitoring IaaS/PaaS/SaaS environments.</li></ul>
Certifications (Highly Preferred)<ul><li>
SANS GIAC (GDAT, GMON, GCIA, GCTI, GCIH)</li><li>
Offsec (OSDA)</li><li>
INE (eCTHP, eCIR)</li><li>
(ISC)&sup2; CISSP, CSSLP 
</li></ul>Soft Skills<ul><li>
Exceptional analytical thinking and creative problem-solving.</li><li>
Excellent communication (English &amp; Arabic), including technical reporting.</li><li>
Strong mentorship abilities and a collaborative spirit.</li><li>
Self-motivated, focused, and passionate about cyber defense.</li>
Capable of juggling priorities under high-pressure situations. 
<li>
</li></ul> 
 
Benefits 
Impact that Matters &ndash; Build products that shape the future of cybersecurity and protect organizations globally.
On-Site Collaboration &ndash; Be at the heart of innovation in our Riyadh office, working side by side with passionate experts.
Continuous Growth &ndash; Access to certifications, trainings, and opportunities to sharpen your expertise.
Ownership Mindset &ndash; Benefit from our ESOP program and grow with COGNNA&rsquo;s success.
Culture of Trust &ndash; We empower talent, encourage ownership, and celebrate real outcomes.</div>

Threat Detection Engineer

Datamatics Global Services Ltd

<div><h1 class="jobSectionHeader">Senior AI Engineer (Arabic Speaker)</h1>
Location: Riyadh, Saudi Arabia 
Experience: 6&ndash;8 Years 
Employment Type: Full-Time / Contract 
Language Requirement: Native or Fluent Arabic Speaker (Mandatory)<h2 class="jobSectionHeader">
About the Role</h2>
We are seeking a highly skilled Senior AI Engineer (Arabic Speaker) to join our growing AI and Data Science team in Riyadh. The ideal candidate will have strong expertise in Artificial Intelligence, Generative AI, Machine Learning Operations (MLOps), and Cloud-based AI Platforms, with proven experience in designing, developing, deploying, and managing enterprise-grade AI solutions.
The successful candidate will play a key role in building scalable AI systems, implementing GenAI applications, operationalizing machine learning models, and collaborating with business stakeholders to deliver innovative AI-driven solutions that create measurable business impact.<h2 class="jobSectionHeader">
Key Responsibilities</h2><h3 class="jobSectionHeader">
AI &amp; Machine Learning Development</h3><ul><li>
Design, develop, train, and deploy machine learning and deep learning models for enterprise use cases.</li><li>
Build and optimize predictive analytics, NLP, recommendation systems, and intelligent automation solutions.</li><li>
Develop AI-powered applications leveraging Large Language Models (LLMs) and Generative AI technologies.</li><li>
Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.</li><li>
Evaluate and benchmark AI models to ensure performance, scalability, and reliability.</li></ul><h3 class="jobSectionHeader">
Generative AI Engineering</h3><ul><li>
Design and implement enterprise GenAI solutions using OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, and other LLM platforms.</li><li>
Develop conversational AI solutions, intelligent assistants, and knowledge management systems.</li><li>
Build prompt engineering frameworks and optimize prompts for business use cases.</li><li>
Implement vector databases and semantic search solutions.</li><li>
Develop AI agents and autonomous workflows using modern AI orchestration frameworks.</li></ul><h3 class="jobSectionHeader">
MLOps &amp; AI Operations</h3><ul><li>
Design and implement end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.</li><li>
Automate model deployment using CI/CD pipelines and infrastructure-as-code practices.</li><li>
Monitor model performance, drift detection, retraining strategies, and operational KPIs.</li><li>
Establish AI governance, model versioning, reproducibility, and compliance standards.</li><li>
Implement scalable AI platforms supporting multiple business units.</li></ul><h3 class="jobSectionHeader">
Cloud &amp; Platform Engineering</h3><ul><li>
Deploy AI/ML workloads on cloud platforms such as Azure, AWS, GCP, or OCI.</li><li>
Manage containerized AI environments using Docker and Kubernetes.</li><li>
Design scalable AI infrastructure supporting high-volume enterprise workloads.</li><li>
Optimize cloud resources, performance, and operational costs.</li></ul><h3 class="jobSectionHeader">
Data Engineering &amp; Integration</h3><ul><li>
Collaborate with data engineering teams to build AI-ready data pipelines.</li><li>
Integrate AI solutions with enterprise applications, APIs, databases, and business platforms.</li><li>
Ensure data quality, security, privacy, and compliance with organizational standards.</li></ul><h3 class="jobSectionHeader">
Stakeholder Management</h3><ul><li>
Engage with business stakeholders to identify AI opportunities and translate business requirements into technical solutions.</li><li>
Present AI solution architectures, recommendations, and project outcomes to technical and non-technical audiences.</li><li>
Mentor junior AI engineers, data scientists, and platform engineers.</li></ul><h2 class="jobSectionHeader">
Required Technical Skills</h2><h3 class="jobSectionHeader">
Artificial Intelligence &amp; Machine Learning</h3><ul><li>
Machine Learning</li><li>
Deep Learning</li><li>
Natural Language Processing (NLP)</li><li>
Predictive Analytics</li><li>
Computer Vision (preferred)</li><li>
Reinforcement Learning (preferred)</li></ul><h3 class="jobSectionHeader">
Generative AI</h3><ul><li>
Large Language Models (LLMs)</li><li>
Retrieval-Augmented Generation (RAG)</li><li>
Prompt Engineering</li><li>
AI Agents &amp; Multi-Agent Systems</li><li>
Fine-Tuning and Model Optimization</li><li>
Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)</li><li>
LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen</li></ul><h3 class="jobSectionHeader">
MLOps</h3><ul><li>
MLflow</li><li>
Kubeflow</li><li>
Airflow</li><li>
Model Monitoring &amp; Observability</li><li>
CI/CD for ML</li><li>
Feature Stores</li><li>
Model Registry</li><li>
Experiment Tracking</li><li>
Model Governance</li></ul><h3 class="jobSectionHeader">
Cloud Platforms</h3><ul><li>
Microsoft Azure</li><li>
AWS</li><li>
Google Cloud Platform (GCP)</li><li>
Oracle Cloud Infrastructure (OCI) &ndash; Preferred</li></ul><h3 class="jobSectionHeader">
Containers &amp; DevOps</h3><ul><li>
Docker</li><li>
Kubernetes</li><li>
Git</li><li>
GitHub Actions</li><li>
Jenkins</li><li>
Terraform</li><li>
Infrastructure as Code</li></ul><h3 class="jobSectionHeader">
Programming Languages</h3><ul><li>
Python (Mandatory)</li><li>
SQL</li><li>
Bash/Shell Scripting</li><li>
Java or C# (Preferred)</li></ul><h2 class="jobSectionHeader">
Qualifications</h2><ul><li>
Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.</li><li>
Master's Degree in AI, Machine Learning, Data Science, or related field is highly preferred.</li></ul><h2 class="jobSectionHeader">
Experience Requirements</h2><ul><li>
6&ndash;8 years of experience in AI/ML Engineering, Data Science, or AI Platform Engineering.</li><li>
Minimum 3+ years of hands-on experience implementing Generative AI solutions.</li><li>
Proven experience building and operationalizing machine learning models in production environments.</li><li>
Strong experience implementing enterprise MLOps frameworks and practices.</li><li>
Experience working with cloud-native AI services and modern AI platforms.</li></ul><h2 class="jobSectionHeader">
Preferred Certifications</h2><ul><li>
Microsoft Azure AI Engineer Associate</li><li>
AWS Machine Learning Specialty</li><li>
Google Professional Machine Learning Engineer</li><li>
OCI AI Foundations Associate</li><li>
Kubernetes Certifications (CKA/CKAD)</li><li>
Databricks Machine Learning Professional</li></ul><h2 class="jobSectionHeader">
Soft Skills</h2><ul><li>
Strong analytical and problem-solving skills.</li><li>
Excellent communication and stakeholder management abilities.</li><li>
Ability to work effectively in cross-functional and multicultural environments.</li><li>
Strong ownership, accountability, and leadership mindset.</li><li>
Passion for innovation and continuous learning.</li><li>
Ability to communicate fluently in both Arabic and English.</li></ul><h2 class="jobSectionHeader">
Mandatory Requirements</h2><ul><li>
Native or Fluent Arabic Speaker.</li><li>
6&ndash;8 years of relevant AI/ML engineering experience.</li><li>
Hands-on expertise in Generative AI and MLOps.</li><li>
Strong Python programming skills.</li><li>
Experience deploying AI solutions in enterprise production environments.</li><li>
Willingness to work onsite in Riyadh, Saudi Arabia.</li></ul>
synAh1U1mw</div>

Senior AI Engineer (Arabic Speaker)

JAWRAA

<div>
 
 Jawraa is a leading digital transformation partner committed to empowering businesses in Saudi Arabia. With over two decades of experience, we've helped organizations navigate the evolving digital landscape and achieve their goals. Our deep industry expertise and strategic partnerships with top-tier technology providers set us apart.
 
 
 
 
 
 
 About the job :
 
 
 
 We are looking for a Senior Cloud Engineer with deep expertise in Google Cloud Platform (GCP) to join our growing engineering team. In this role, you will be responsible for designing, building, and maintaining scalable, secure, and highly available cloud infrastructure that powers our core products and services. You will partner with software engineers, data teams, and security to lead cloud-native transformation initiatives and champion best practices across the organization.
 
 
 
 
 
 
 Key Responsibilities :
 
 
 
 
 Infrastructure Architecture &amp; Design
 
 
 
 &bull; Architect and implement highly available, fault-tolerant, and scalable cloud solutions on GCP
 
 
 &bull; Lead the design of GCP-native infrastructure using services such as GKE, Cloud Run, Compute Engine, Cloud SQL, BigQuery, Pub/Sub, and Cloud Storage
 
 
 &bull; Define infrastructure standards, patterns, and reference architectures for engineering teams
 
 
 
 
 
 
 DevOps &amp; Automation
 
 
 
 &bull; Build and maintain Infrastructure as Code (IaC) using Terraform and Google Deployment Manager
 
 
 &bull; Design and manage CI/CD pipelines using Cloud Build, GitHub Actions, or similar tooling
 
 
 &bull; Automate cloud operations, monitoring, and remediation using scripting (Python, Bash, Go)
 
 
 
 
 
 
 Security &amp; Compliance
 
 
 
 &bull; Implement and enforce GCP security best practices including IAM, VPC Service Controls, and Cloud Armor
 
 
 &bull; Ensure compliance with regulatory frameworks (SOC 2, ISO 27001, GDPR) within the cloud environment
 
 
 &bull; Conduct regular security assessments and drive vulnerability remediation efforts
 
 
 
 
 
 
 Reliability &amp; Performance
 
 
 
 &bull; Define and maintain SLIs, SLOs, and error budgets for cloud infrastructure services
 
 
 &bull; Lead incident response, root cause analysis, and blameless post-mortems
 
 
 &bull; Optimize cloud resource utilization and drive cost management through FinOps practices
 
 
 
 
 
 
 Collaboration &amp; Leadership
 
 
 
 &bull; Mentor junior and mid-level cloud engineers and promote a culture of learning
 
 
 &bull; Collaborate with product, data, and security teams to align cloud strategy with business goals
 
 
 &bull; Document architecture decisions, runbooks, and operational procedures
 
 
 
 
 
 
 Google Cloud Networking
 
 
 
 &bull; Design and manage Google Cloud VPC networks, subnets, firewall rules, and network policies
 
 
 &bull; Configure and optimize Cloud Load Balancing (HTTP(S), TCP/SSL, Internal) for high-availability workloads
 
 
 &bull; Implement Cloud CDN, Cloud DNS, and Traffic Director for global traffic management
 
 
 &bull; Set up and manage hybrid connectivity using Cloud Interconnect (Dedicated &amp; Partner) and Cloud VPN
 
 
 &bull; Deploy and configure Shared VPC and VPC Network Peering for multi-project architectures
 
 
 &bull; Apply network security controls including Cloud Armor (WAF/DDoS), VPC Service Controls, and Private Google Access
 
 
 &bull; Monitor and troubleshoot network performance using Network Intelligence Center, Connectivity Tests, and VPC Flow Logs
 
 
 &bull; Design private networking for GKE clusters using Alias IP ranges, Cloud NAT, and Private Service Connect
 
 
 
 
 
 
 Requirements :
 
 
 
 &bull; Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field &mdash; or equivalent practical experience.
 
 
 &bull; 7+ years of experience in cloud engineering, with at least 5 years hands-on with GCP
 
 
 &bull; Deep expertise in GCP services: GKE, Cloud Run, BigQuery, Pub/Sub, Cloud Functions, VPC, IAM
 
 
 &bull; Proficiency in Infrastructure as Code using Terraform
 
 
 &bull; Strong programming/scripting skills in Python, Go, or Bash
 
 
 &bull; Experience with Kubernetes and containerized workloads
 
 
 &bull; Hands-on experience with CI/CD tooling and GitOps workflows
 
 
 &bull; Solid understanding of networking concepts: DNS, VPNs, load balancing, CDN, TCP/IP
 
 
 &bull; Experience implementing security controls and compliance in cloud environments
 
 
 &bull; Google Cloud Professional certifications (Cloud Architect, DevOps Engineer, Security Engineer)
 
 
 &bull; Experience with multi-cloud or hybrid cloud architectures
 
 
 &bull; Familiarity with data engineering tools: Dataflow, Dataproc, BigQuery ML
 
 
 &bull; Experience with service mesh technologies (Istio, Anthos Service Mesh)
 
 
 &bull; Background in SRE principles and practices
 
 
 
 
 
 
 
 
 
 Required Specialized Certifications :
 
 
 
 Google Professional Cloud Architect
 
 
 Google Professional DevOps Engineer
 
 
 Google Professional Cloud Security Engineer
 
 
 Google Associate Cloud Engineer
 
</div>

Senior Cloud Engineer {GCP}

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Artificial Intelligence Engineer

Artificial Intelligence Engineer

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AI Solution, Engineer

Threat Detection Engineer

Senior AI Engineer (Arabic Speaker)

Senior Cloud Engineer {GCP}