environmental engineer

electrical engineer

elv technician

instrumentation engineer

mechanical engineer

machine learning engineer

Mowasalat Qatar

<div>
 
 
 Job Summary
 
 
 
 The Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models and data‑driven solutions to support Mowasalat&rsquo;s business optimization and digital transformation initiatives. The role focuses on translating complex data into actionable insights, collaborating with cross‑functional teams, and ensuring scalable, reliable, and high‑performing machine learning solutions that drive operational and strategic value.
 
 
 
 
 
 
 
 Main Responsibilities
 
 
 
 
 
 
 
 
 Machine Learning Model Development &amp; Deployment
 
 
 <ul>
 <li>
 Design, develop, test, and deploy machine learning models using supervised, unsupervised, and reinforcement learning techniques.
 </li>
 <li>
 Perform exploratory data analysis, feature engineering, and model tuning to improve accuracy, reliability, and scalability.
 </li>
 <li>
 Continuously evaluate and refine models to ensure optimal performance and alignment with business objectives.
 </li>
 </ul>
 
 
 
 
 
 Data Pipeline Management
 
 
 <ul>
 <li>
 Collaborate with data engineers to design, implement, and maintain data pipelines for model training and deployment.
 </li>
 <li>
 Ensure data quality, integrity, security, and availability across all machine learning workflows.
 </li>
 <li>
 Troubleshoot data pipeline issues and optimize data flow for efficient model operations.
 </li>
 </ul>
 
 
 
 
 
 Model Evaluation &amp; Performance Monitoring
 
 
 <ul>
 <li>
 Conduct comprehensive model validation, testing, and performance evaluation.
 </li>
 <li>
 Monitor deployed models for performance degradation or data drift and implement corrective actions as required.
 </li>
 <li>
 Measure and report the impact of machine learning solutions on business outcomes.
 </li>
 </ul>
 
 
 
 
 
 Stakeholder Collaboration &amp; Business Alignment
 
 
 <ul>
 <li>
 Work closely with business stakeholders to understand requirements and translate them into data‑driven solutions.
 </li>
 <li>
 Communicate complex technical concepts and analytical findings to non‑technical audiences in a clear and effective manner.
 </li>
 <li>
 Collaborate with cross‑functional teams to integrate machine learning solutions into business operations and ensure adoption.
 </li>
 </ul>
 
 
 
 
 
 Innovation &amp; Continuous Improvement
 
 
 <ul>
 <li>
 Stay up to date with emerging machine learning technologies, tools, and industry best practices.
 </li>
 <li>
 Research and evaluate new techniques, frameworks, and methodologies to drive innovation and enhance solution effectiveness.
 </li>
 <li>
 Support continuous improvement initiatives within data science and AI capabilities.
 </li>
 </ul>
 
 
 
 
 
 
 Qualifications, Certificates &amp; Skills
 
 
 
 
 
 
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Mathematics, Statistics, or a related field.
 </li>
 </ul>
 
 
 
 
 
 Experience
 
 
 <ul>
 <li>
 Minimum
 
 6&ndash;8 years
 
 of experience in machine learning, data science, or a related field.
 </li>
 <li>
 Preferably with experience in the
 
 transportation sector
 
 .
 </li>
 <li>
 
 2&ndash;3 years of GCC experience
 
 in a similar or equivalent role within a reputed organization.
 </li>
 <li>
 Proven experience in developing and deploying machine learning models in production environments.
 </li>
 </ul>
 
 
 
 
 
 Certifications &amp; Training
 
 (Preferred)
 
 
 
 <ul>
 <li>
 Certified Machine Learning Engineer (CMLE)
 </li>
 <li>
 TensorFlow Developer Certificate
 </li>
 <li>
 Certified Data Scientist (CDS) or equivalent
 </li>
 </ul>
 
 
 
 
 
 Skills
 
 
 <ul>
 <li>
 Machine Learning Algorithms &amp; Model Development
 </li>
 <li>
 Programming Languages:
 
 Python, R, or Julia
 
 </li>
 <li>
 ML Frameworks:
 
 TensorFlow, PyTorch, Scikit‑learn
 
 </li>
 <li>
 Data Analysis &amp; Visualization:
 
 Pandas, NumPy, Matplotlib, Seaborn
 
 </li>
 <li>
 Data Pipeline &amp; Model Deployment
 </li>
 <li>
 Cloud Platforms:
 
 AWS, Azure, or Google Cloud
 
 </li>
 <li>
 Analytical Thinking &amp; Problem‑Solving
 </li>
 <li>
 Communication &amp; Stakeholder Collaboration
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer - Qatarization

QatarEnergy

<div>
 
 Primary Purpose Of The Job
 
 
 
 We are seeking a highly skilled AI/BI Engineer with a strong background in machine learning, AI, and business intelligence. The ideal candidate will be responsible for designing and deploying scalable AI and ML solutions that supports informed decision-making across the organization.
 
 
 You will build and integrate AI-powered applications, particularly those leveraging large language models (LLMs), developing interactive dashboards, integrating LLMs into BI platforms and predictive models to enhance business insights and improve user experience.
 
 
 
 Required Experience And Skills
 
 
 
 <ul>
 <li>
 Minimum 8 years of experience in Data Science, AI Engineering, advanced analytics, or related roles; Oil and Gas industry experience is a plus.
 </li>
 <li>
 Experience in developing AI solutions using cloud platforms such as Microsoft Azure, AWS, or GCP, and tools like AI Foundry, Copilot Studio, Vertex AI Studio, and Databricks Mosaic AI.
 </li>
 <li>
 Design and deploy AI/ML models and LLM-powered applications to support business use cases and enhance decision-making.
 </li>
 <li>
 Integrate AI/ML models and LLM capabilities into BI platforms to enable natural language querying, automated insights, and conversational analytics.
 </li>
 <li>
 Evaluate and optimize LLM-generated responses to ensure accuracy and relevance.
 </li>
 <li>
 Deep understanding of AI/ML algorithms, LLMs, and modern AI architectures.
 </li>
 <li>
 Proficiency in Python, SQL and AI/ML frameworks such as Hugging Face, LangChain, scikit-learn, TensorFlow, PyTorch and Semantic Kernel etc.
 </li>
 <li>
 Develop compelling data visualizations and dashboards to support storytelling and real-time insights.
 </li>
 <li>
 Ensure compliance with data governance, model explainability, and ethical AI practices, including data lineage, access control, and sensitivity labeling.
 </li>
 <li>
 Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML workflows.
 </li>
 <li>
 Excellent communication skills, with an ability to effectively interact with business stakeholders and articulate complex technical concepts in a clear and understandable manner.
 
 
 </li>
 </ul>
 
 Educational Qualifications
 
 
 
 A bachelor&rsquo;s degree in computer science, Data Science, Artificial Intelligence, or a related field.
 
 
 Master&rsquo;s degree preferred, especially with a focus on AI or Machine Learning
</div>

SR. BUSINESS ANALYST (ANALYTICS)

Saher Management Consultancies LLC

<div>
 
 Role:
 
 
 Experience Level: 10+ Years
 
 
 
 
 location: QATAR
 
 
 
 
 Note :communication (Arabic &amp; English). Gulf nationals only.
 
 
 
 
 Machine Learning &amp; Generative AI Engineer (Mid-Level)
 
 
 
 
 ML | DL | Python | LangChain/LangGraph | Azure AI Foundry | RAG | Vector Stores | Semantic Kernel
 
 
 Role Summary
 
 
 Build and deploy enterprise-grade Generative AI solutions with strong grounding and
 
 
 measurable quality. You will implement RAG pipelines, agentic workflows
 
 
 (LangChain/LangGraph/ Semantic Kernel), and evaluation/monitoring on Azure AI Foundry
 
 
 and Azure services, or GCP.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Implement end-to-end RAG: ingestion, chunking, embeddings, retrieval, reranking,
 
 
 </li>
 </ul>
 and citation/grounding.
 
 
 <ul>
 <li>
 Develop agentic workflows using Semantic Kernel, LangChain and LangGraph
 
 
 </li>
 </ul>
 (tools, routing, memory) with guardrails and safe tool use.
 
 
 <ul>
 <li>
 Integrate vector stores/search (Azure AI Search vector, Pinecone, Weaviate, Milvus,
 
 
 </li>
 </ul>
 pgvector, or equivalent) and maintain reliable data pipelines.
 
 
 <ul>
 <li>
 Build Python services/APIs (FastAPI preferred) with streaming, auth (Entra ID/OIDC
 
 
 </li>
 </ul>
 as applicable), and production-ready error handling.
 
 
 <ul>
 <li>
 Own quality and operations: golden datasets, automated regression evaluation,
 
 
 </li>
 </ul>
 tracing/observability, and latency/cost optimization (caching, batching).
 
 
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 3-6 years software engineering experience; 1-3 years delivering ML/GenAI features
 
 
 </li>
 </ul>
 to production.
 
 
 <ul>
 <li>
 Strong Python, API development, unit/integration testing, and Git-based workflows
 
 
 </li>
 </ul>
 (Azure DevOps or GitHub).
 
 
 <ul>
 <li>
 Hands-on experience with RAG patterns, embeddings, retrieval strategies, prompt
 
 
 </li>
 </ul>
 design, and LLMs evaluation basics.
 
 
 <ul>
 <li>
 Experience with Azure AI Foundry / Azure OpenAI and deploying on Azure
 
 
 </li>
 </ul>
 (Container Apps, Functions, App Service,
 
 
 <ul>
 <li>
 or AKS).
 </li>
 <li>
 Comfortable working with data and documents; strong communication and
 
 
 </li>
 </ul>
 documentation skills.
 
 
 Great Advantage
 
 
 <ul>
 <li>
 LLMOps: prompt/version governance, tracing (LangSmith/OpenTelemetry), and
 
 
 </li>
 </ul>
 evaluation frameworks.
 
 
 <ul>
 <li>
 Hybrid search and reranking, structured outputs (JSON schema), and prompt-
 
 
 </li>
 </ul>
 injection/tool-safety mitigations.
 
 
 <ul>
 <li>
 Performance testing and cost optimization experience for LLM-based systems.
 </li>
 <li>
 Bilingual communication (Arabic &amp; English).
 
 
 </li>
 </ul>
 Typical Tech Stack
 
 
 <ul>
 <li>
 Python (FastAPI), LangChain, LangGraph, Azure AI Foundry, Azure OpenAI, Azure AI
 
 
 </li>
 </ul>
 Search (vector), Semantic Kernel, PyTroch, Keras, Tensorflow.
 
 
 <ul>
 <li>
 Pinecone/Weaviate /pgvector / Azure AI Search, Docker, Azure DevOps, Key Vault,
 
 
 </li>
 </ul>
 Application Insights.
 
 
 
 Skills: vector,python,rag,kernel,ml,azure
</div>

Machine Learning & Generative AI Engineer

DOHA BANK

<div>
 
 
 Role Objective
 
 
 
 The incumbent will support business units in designing, developing, and maintaining
 
 AI-driven applications, machine learning models, analytics solutions, and automation tools
 
 , ensuring alignment with business requirements and digital architecture.
 
 
 
 
 
 They will collaborate with stakeholders in implementing AI frameworks, improving existing AI functionality, conducting testing, optimizing performance, and ensuring secure and compliant AI solution delivery within the bank.
 
 
 
 
 
 
 Detailed Roles and Responsibilities
 
 
 
 
 
 
 
 OPERATIONAL
 
 
 <ul>
 <li>
 Collaborate with Business Intelligence, business units, and relevant stakeholders to analyze requirements and design AI‑based features and solutions.
 </li>
 <li>
 Stay updated on emerging AI/ML technologies, frameworks, and methodologies.
 </li>
 <li>
 Apply modern AI/ML frameworks to optimize solution performance, ensure model accuracy, and support innovation.
 </li>
 <li>
 Contribute to the full AI project lifecycle: data gathering, feature engineering, model building, model validation, deployment, and monitoring.
 </li>
 <li>
 Work with the Senior Specialist to plan and implement system development/enhancement projects, including scope definition and scheduling.
 </li>
 <li>
 Document business requirements, functional specifications, and technical designs.
 </li>
 <li>
 Develop scripts, programming logic, and AI components required for new solutions or enhancements.
 </li>
 <li>
 Deliver prototypes and proofs of concept based on user requirements and feasibility assessments.
 </li>
 <li>
 Conduct unit, integration, and performance testing of AI applications to ensure alignment with approved design and bank standards.
 </li>
 <li>
 Troubleshoot AI models, data pipelines, and application bugs, ensuring timely resolution.
 </li>
 <li>
 Execute system improvements and upgrades as per approved schedules.
 </li>
 <li>
 Prepare management and progress reports on AI‑related development and enhancements.
 </li>
 <li>
 Assist in feasibility assessments, data mapping, data processing, and dataset preparation for AI and machine learning initiatives.
 </li>
 <li>
 Ensure strict adherence to
 
 data privacy
 
 ,
 
 model governance
 
 , and
 
 security frameworks
 
 when handling sensitive banking data.
 </li>
 <li>
 Work with Data Operations to automate business processes using AI, ML, and scripting.
 </li>
 <li>
 Collaborate with Data Governance and Data Operations teams to ensure secure data operations and high‑quality datasets used in model training.
 </li>
 <li>
 Monitor database and AI pipeline performance, perform tuning, and implement improvements.
 </li>
 <li>
 Maintain strict confidentiality, ethics, and professional conduct.
 </li>
 <li>
 Follow the bank&rsquo;s audit, risk, compliance, and internal control frameworks.
 </li>
 </ul>
 
 
 
 
 
 Experience
 
 
 <ul>
 <li>
 5&ndash;8 years of total experience in the financial services or banking industry in relevant technical roles.
 </li>
 <li>
 Prior hands‑on experience developing AI applications, ML models, or intelligent automation tools.
 </li>
 <li>
 Experience with Oracle, Python, cloud‑based ML platforms, and enterprise data management.
 </li>
 </ul>
 
 
 
 
 
 Technical Competencies
 
 
 
 
 Core Skills
 
 
 <ul>
 <li>
 Business requirements analysis
 </li>
 <li>
 System analysis, design, and programming
 </li>
 <li>
 Strong proficiency in AI/ML development (Python, TensorFlow, PyTorch, Scikit‑learn)
 </li>
 <li>
 Experience with cloud ML platforms (Azure ML, AWS Sagemaker, GCP Vertex)
 </li>
 <li>
 Proficiency in conversational AI tools and generative AI frameworks
 </li>
 <li>
 Knowledge of report‑building tools and BI development
 </li>
 <li>
 Knowledge of data marts, ETL processes, and database security
 </li>
 <li>
 Familiarity with front‑end tools for forms, dashboards, and app deployment
 </li>
 <li>
 Hands‑on experience with Microsoft BI tools
 </li>
 <li>
 MIS report development
 </li>
 <li>
 Understanding of software development best practices
 </li>
 <li>
 Ability to independently troubleshoot application and model issues
 </li>
 <li>
 Strong analytical and problem‑solving skills
 </li>
 </ul>
 
 
 
 
 
 Regulatory Compliance
 
 
 <ul>
 <li>
 Knowledge of banking regulatory frameworks
 </li>
 <li>
 Awareness of AI ethics, data privacy rules, and model governance guidelines
 </li>
 </ul>
 
 
 
 
 
 Certifications (Preferred)
 
 
 <ul>
 <li>
 AI, ML, Data Science, Cloud AI, or equivalent certifications
 </li>
 </ul>
 
 
 
 
 
 IMPORTANT
 
 
 
 
 Industry Knowledge
 
 
 <ul>
 <li>
 Knowledge of banking products, services, and operational flows
 </li>
 <li>
 Understanding of global/local AI market trends in financial services
 </li>
 </ul>
</div>

Technical Developer AI Application

Visa

<div>Company Description 
Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose &ndash; to uplift everyone, everywhere by being the best way to pay and be paid.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. 
Job Description 
<ul><li>
Identify innovation opportunities around data and data-related processes that will help our clients implement fact-based decisioning processes within their cards and payments program</li><li>
Work entails heavy focus on transaction data modelling and analytics for cards and payments products Work with a broader team that consists of Business Managers, Consultants and Data Scientists from both Visa and client organizations to strategies, co-create, deploy, and reap the benefits of data-driven solutions.</li><li>
Work with regional and global Data Science teams to develop high-quality analytic products and solutions that promote Visa&rsquo;s growth in the region.</li><li>
Keep Visa at the forefront of technological advancement in Data Science by introducing cutting-edge tools and techniques for generating business insights</li><li>
Develop next-generation analytic methods where existing tools and techniques are inadequate to address business challenges</li><li>
Review, direct, guide, and inspire the analytical work of junior members in the team</li><li>
Collaborate with internal Technology partners and Data Engineering function to best leverage Visa&rsquo;s internal technology platforms, data, and the broader Visa ecosystem to support our clients&rsquo; technical data needs</li><li>
Manage workload for self and any direct reports, providing prioritization guidance for project flow to improve process efficiency.</li><li>
Manage and grow talent within the team.</li><li>
Develop, share, and build global best practices and knowledge management within the team</li><li>
Socialize innovative ideas and approaches that are scalable and have market demand</li><li>
Champion internal requirements around Model Risk Management, Visa Analytics Rules, and Global Privacy standards around client delivery to ensure that Visa&rsquo;s highly regarded market standing is maintained</li></ul>
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 
Qualifications 
<ul><li>
Minimum of 6+ years of expertise in applying Machine Learning solutions to business problems &ndash; model development and production experience required</li><li>
Post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering</li><li>
Experience working in one or more of the Card &amp; Payments markets around the globe with specific responsibilities in payments, retail banking, or retail merchant industries</li><li>
Good understanding of Payments and the Banking industry, including card verticals such as consumer credit, consumer debit, prepaid, small business, commercial and co-branded product</li><li>
Expert knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies, with demonstrated ability to incorporate new techniques to solve business problems</li><li>
Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams, including resource planning and delivery implementation Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels</li><li>
Proven ability to deliver results within committed scope, timeline, and budget</li><li>
Very strong people/project management skills and experience</li><li>
Ability to travel within MENA on short notice</li></ul>
Technical Expertise<ul><li>
Expertise in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.).</li><li>
Familiarity with both common computing environments (e.g., Linux, Shell Scripting) and commonly used IDE&rsquo;s (Jupyter Notebooks) proficiency in SAS technologies and techniques</li><li>
Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, and SQL. Working knowledge of GENAI and Agentic AI tools and algorithms</li><li>
Proficient in some or all of the following techniques: Linear &amp; Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, etc.</li><li>
Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial, and multinomial regression, ANOVA) Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis) Decision Tree techniques (e.g., CART, CHAID)</li></ul> 

Additional Information 
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.</div>

GCC Data Science Manager

Arab Solutions

<div>
 
 Job Title: Data Scientist &ndash; Population &amp; Demographic Modeling
 
 
 Role Overview
 
 
 
 The Data Scientist will lead the development and management of population and demographic models to forecast demographic dynamics and support long-term strategic planning. The role complements economic modeling by applying advanced data science, machine learning, and forecasting techniques to strengthen economic foresight, scenario planning, and policy decision-making within the Strategic Foresight Department.
 
 
 
 Key Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and maintain population and demographic models (e.g., cohort-component models) to project fertility, mortality, and migration trends.
 </li>
 <li>
 Lead demographic data analysis using census, survey, administrative, and alternative data sources.
 </li>
 <li>
 Build and manage scalable data pipelines integrating multi-source demographic and economic datasets.
 </li>
 <li>
 Support macroeconomic modeling and forecasting through advanced statistical, econometric, and machine learning techniques.
 </li>
 <li>
 Collaborate with economists, foresight researchers, and scenario planners to integrate demographic and economic projections into foresight scenarios.
 </li>
 <li>
 Produce population outlooks, trend analyses, and interactive dashboards to inform government planning and policy development.
 </li>
 <li>
 Ensure data quality, model transparency, validation, and reproducibility.
 </li>
 <li>
 Maintain comprehensive documentation of methodologies, assumptions, and analytical outputs.
 </li>
 <li>
 Provide technical training and knowledge transfer on population modeling and data science methods.
 </li>
 <li>
 Explore innovative approaches including AI/ML, big data, geospatial analysis, and simulation techniques to enhance forecasting accuracy.
 </li>
 <li>
 Ensure structured handover and sustainability of all analytical models and tools.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree or PhD in Data Science, Statistics, Computer Science, Demography, or a related field.
 </li>
 <li>
 4+ years of experience in population modeling, demographic forecasting, or applied data science.
 </li>
 <li>
 Demonstrated expertise in population modeling and demographic data analysis.
 </li>
 <li>
 Experience working with government, public sector entities, think tanks, or international organizations is strongly preferred.
 </li>
 <li>
 Experience working with large-scale, policy-driven datasets is an advantage.
 
 
 </li>
 </ul>
 
 Technical Competencies
 
 
 
 <ul>
 <li>
 Proficiency in Python and/or R for statistical and demographic modeling.
 </li>
 <li>
 Strong experience with machine learning, simulation, and predictive analytics.
 </li>
 <li>
 Experience with cloud data platforms such as AWS, Azure, or CDP environments.
 </li>
 <li>
 Strong data management and querying skills (e.g., SQL).
 </li>
 <li>
 Proficiency in data visualization and dashboarding tools (e.g., Power BI, Tableau).
 </li>
 <li>
 Strong proficiency in Microsoft Office, especially Excel and PowerPoint for policy-oriented reporting.
 
 
 </li>
 </ul>
 
 Language Requirements
 
 
 
 <ul>
 <li>
 Fluent in Arabic and English, both written and spoken.
 
 
 </li>
 </ul>
 
 Soft Skills
 
 
 
 <ul>
 <li>
 Strong analytical, critical thinking, and problem-solving abilities.
 </li>
 <li>
 High attention to detail with a strong commitment to data integrity and research quality.
 </li>
 <li>
 Ability to collaborate effectively across multidisciplinary teams.
 </li>
 <li>
 Skilled at translating complex analytical findings into clear, actionable insights for policymakers.
 </li>
 <li>
 Innovative, adaptive, and curious, with a strong interest in emerging tools and methodologies.
 
 
 </li>
 </ul>
 Skills: advanced statistical,machine learning techniques,ai/ml,foresight scenarios,aws,geospatial analysis,cloud data,cdp environments,big data,azure,data quality,econometric,data pipelines,python
</div>

Data Scientist (Arabic)

Starlink Qatar

<div>
 📌 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻:
 
 
 We are seeking a visionary AI Architect to lead the design and delivery of transformative, enterprise-grade AI solutions. In this role, you will be pivotal in shaping the future of sports, healthcare, and education by architecting and implementing cutting-edge systems. You will translate complex business challenges into robust, scalable AI solutions using platforms like Azure AI Foundry and Google Agent Builder. Your work will involve deep integration with core enterprise systems, including ERP and CRM, ensuring our AI initiatives deliver measurable real-world impact. As a key leader, you will establish AI governance frameworks, championing ethical and transparent practices. You will apply a broad range of techniques, from NLP and computer vision to multi-agent systems, to optimize outcomes and drive innovation. This position requires a strategic thinker with deep technical expertise, capable of defining KPIs and demonstrating the tangible ROI of AI deployments. Join us to build next-generation AI solutions that make a difference.
 
 
 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 
 
 🎯 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀:
 
 
 &rtrif; Minimum 8 years in solution architecture, with at least 4 years in applied AI/ML.
 
 
 &rtrif; Demonstrated expertise in architecting scalable AI/ML solutions using Azure AI Foundry and/or Google Agent Builder.
 
 
 &rtrif; Proven experience integrating AI systems with enterprise platforms such as ERP, CRM, medical, or sports performance systems.
 
 
 &rtrif; Advanced knowledge of data architecture, including RAG, knowledge graphs, SQL, NoSQL, and vector databases.
 
 
 &rtrif; Hands-on experience applying NLP, computer vision, and predictive analytics to solve business problems.
 
 
 &rtrif; Strong ability to translate complex business cases and requirements into technical AI solution designs.
 
 
 &rtrif; Bachelor&rsquo;s degree in AI, Data Science, Computer Science, Engineering, or a related field.
 
 
 &rtrif; Experience in implementing governance frameworks for AI transparency, compliance, and ethics.
 
 
 ✨ 𝗗𝗲𝘀𝗶𝗿𝗮𝗯𝗹𝗲𝘀:
 
 
 &rtrif; Master&rsquo;s or PhD in a relevant field.
 
 
 &rtrif; Certifications such as Microsoft AI Architect, Azure AI Foundry, or Google Cloud Professional Machine Learning Engineer.
 
 
 &rtrif; Direct industry experience in sports, healthcare, or education.
 
 
 &rtrif; Experience designing and implementing multi-agent systems.
 
 
 &rtrif; Proven track record of defining KPIs, monitoring AI model performance, and tracking ROI.
 
 
 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 
 
 🚀 𝗧𝗮𝗸𝗲 𝘁𝗵𝗲 𝗟𝗲𝗮𝗽 𝗧𝗼𝘄𝗮𝗿𝗱 𝗮𝗻 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗙𝘂𝘁𝘂𝗿𝗲 &ndash; 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄! 🚀
</div>

AI Architect

Explore 404+ Machine learning engineer in Doha this February. Find roles across top companies and apply now to boost your career.