qa/qc engineer

planning engineer

project engineer

sales engineer

senior structural engineer

ai engineer

Commercial Bank

<div>
 
 About Commercial Bank Of Qatar
 
 
 
 Commercial Bank, founded in 1975 and headquartered in Doha, plays a vital role in Qatar&rsquo;s economic development by offering a range of personal, business, government, international and investment services.
 
 
 We believe in empowering our employees, providing them with opportunities for growth and professional development.
 
 
 By Joining us, you&rsquo;ll be part of a workplace culture that fosters innovation, supports work-life balance, and encourages you to reach your full potential.
 
 
 Join us in shaping the future of banking!
 
 
 
 Job Summary
 
 
 
 The AI Engineer is responsible for designing, developing, and deploying Agentic AI solutions and AI-enabled platforms within the Data &amp; AI Lab. This role focuses on building robust AI infrastructure including integrations with cloud platforms, vector stores, document processing pipelines, and real-time data streaming capabilities.
 
 
 The position requires strong engineering skills to work with AI orchestration frameworks (MCP), cloud services (Azure, GCP), and modern AI tooling. The AI Engineer will collaborate closely with AI Product Owners, Data Scientists, and other engineers to deliver production-grade AI solutions that support banking operations and customer-facing applications.
 
 
 The role bridges AI research and production deployment, ensuring that AI capabilities are scalable, maintainable, and aligned with enterprise architecture standards.
 
 
 
 
 Key Accountabilities
 
 
 
 
 <ul>
 <li>
 Agentic AI Development
 </li>
 <li>
 Design and implement Agentic AI solutions including autonomous workflows, multi-agent systems, and AI orchestration patterns.
 </li>
 <li>
 Develop and maintain integrations with Model Context Protocol (MCP) and similar AI orchestration frameworks.
 </li>
 <li>
 Build and optimize AI pipelines that combine multiple AI capabilities into cohesive solutions.
 </li>
 <li>
 AI Platform Engineering
 </li>
 <li>
 Develop and maintain AI platform components including vector stores, embedding pipelines, and retrieval systems.
 </li>
 <li>
 Implement document parsing, processing, and metadata extraction pipelines for knowledge management and RAG applications.
 </li>
 <li>
 Build and maintain APIs and integration layers for AI services consumption across banking applications.
 </li>
 <li>
 Cloud &amp; Infrastructure
 </li>
 <li>
 Design and deploy AI solutions on cloud platforms (Azure, GCP) following best practices for scalability and security.
 </li>
 <li>
 Implement data streaming architectures using Kafka for real-time AI applications and event-driven AI workflows.
 </li>
 <li>
 Manage AI infrastructure including model serving on OpenShift/Kubernetes, monitoring, and performance optimization.
 </li>
 <li>
 Integration &amp; Delivery
 </li>
 <li>
 Develop RESTful APIs and integration patterns for AI services consumption by internal and external applications.
 </li>
 <li>
 Collaborate with IT teams to integrate AI capabilities into existing banking systems and workflows.
 </li>
 <li>
 Participate in Agile delivery processes (Scrum, Kanban), contributing to sprint planning, code reviews, and continuous improvement.
 </li>
 <li>
 Quality &amp; Standards
 </li>
 <li>
 Ensure AI solutions comply with the bank's security, governance, and regulatory requirements.
 </li>
 <li>
 Maintain code quality through testing, documentation, CI/CD practices, and adherence to engineering best practices.
 </li>
 <li>
 Stay current with emerging AI technologies, tools, and frameworks to continuously improve delivery capabilities.
 
 
 </li>
 </ul>
 
 Key Competencies
 
 
 
 <ul>
 <li>
 AI &amp; ML Engineering
 </li>
 <li>
 Strong understanding of LLMs, embedding models, and generative AI architectures.
 </li>
 <li>
 Experience with AI orchestration frameworks, agent development, and multi-step AI workflows.
 </li>
 <li>
 Familiarity with vector databases (Azure AI Search, Pinecone, Weaviate, Milvus) and RAG patterns.
 </li>
 <li>
 Knowledge of deep learning frameworks (TensorFlow, PyTorch) and model deployment tools (MLflow, TFX).
 </li>
 <li>
 Software Engineering
 </li>
 <li>
 Python (Advanced level) and relevant AI/ML libraries (LangChain, LlamaIndex, or similar).
 </li>
 <li>
 Experience with API development (REST) and microservices architecture.
 </li>
 <li>
 SQL &ndash; Advanced user (Stored Procedures, Window functions, Temp Tables, Recursive Queries).
 </li>
 <li>
 Git (GitHub/GitLab) for version control and code management.
 </li>
 <li>
 Cloud &amp; Data Engineering
 </li>
 <li>
 Experience with cloud platforms (Azure, GCP) and object storage (S3, GCS, ABS).
 </li>
 <li>
 Knowledge of data streaming technologies (Kafka) and workflow orchestration (Airflow, Apache NiFi).
 </li>
 <li>
 Containerization and orchestration: Docker, K8s (OpenShift).
 </li>
 <li>
 Familiarity with Spark for data processing and MLOps practices.
 </li>
 <li>
 Collaboration
 </li>
 <li>
 Ability to work effectively in cross-functional teams with Data Scientists, ML Engineers, and Product Owners.
 </li>
 <li>
 Strong communication skills to explain technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience working in Agile/Scrum environments (Kanban, Scrum).
 
 
 </li>
 </ul>
 
 Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field.
 </li>
 <li>
 4-6 years of experience in software engineering with at least 2 years focused on AI/ML applications.
 </li>
 <li>
 Hands-on experience with cloud platforms (Azure or GCP) and containerization (Docker, OpenShift/K8s).
 </li>
 <li>
 Experience with document processing, metadata extraction, and knowledge management systems preferred.
 </li>
 <li>
 Banking or financial services industry experience is a plus.
 </li>
 <li>
 Relevant certifications (Azure AI Engineer, GCP ML Engineer) preferred.
 
 
 </li>
 </ul>
 
 
 Why Commercial Bank?
 
 
 
 
 <ul>
 <li>
 Best Digital Bank in the Middle East 2024 by World Finance and Best Mobile Banking App in the Middle East 2024 by Global Finance.
 </li>
 <li>
 An Innovation-Driven, Digital-First Environment where employees work with the latest tools and technologies to redefine banking
 </li>
 <li>
 Opportunities for Global Partnerships &amp; International Exposure, connecting employees with global networks and perspectives.
 </li>
 <li>
 A focus on Employee Well-being &amp; Work-Life Balance, ensuring a healthy and supportive environment for all team members
 </li>
 <li>
 Competitive Compensation &amp; Benefits that ensure our employees are rewarded for their dedication and performance
 </li>
 <li>
 A strong Commitment to Diversity, Equity &amp; Inclusion, fostering a culture that values every individual&rsquo;s unique perspective.
 
 
 </li>
 </ul>
 At Commercial Bank, we don&rsquo;t just offer careers, We shape futures by pioneering
 
 digital transformation
 
 in Qatar&rsquo;s banking sector, blending
 
 digital-first
 
 approach to redefine banking through
 
 innovative
 
 solutions.
 
 
 
 Disclaimer
 
 
 
 We appreciate your interest in joining CBQ! Please note that only selected candidates will be contacted for further steps in the hiring process. This job posting is for informational purposes only, and CBQ reserves the right to modify, withdraw, or close it at any time without notice.
</div>

AI Engineer

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)

QNB Group

<div>
 
 About QNB
 
 
 
 Established in 1964 as the country&rsquo;s first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.
 
 
 QNB Group&rsquo;s presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.
 
 
 QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard &amp; Poor&rsquo;s (A), Moody&rsquo;s (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.
 
 
 Based on the Group&rsquo;s consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.
 
 
 QNB Group has an active community support program and sponsors various social, educational and sporting events.
 
 
 
 Job Summary
 
 
 
 The data scientist plays a crucial role in driving advanced analytics and AI initiatives across the bank. This role collaborates closely with business and operational leaders to provide expert support, leveraging data analytical and AI tools to deliver strategic insights and actionable recommendations. Through hypothesis-based analysis to machine learning (ML) projects and applying Large Language Models, the data scientist models complex business problems using a variety of techniques including Predictive or prescriptive analytics, deep learning, GenAI and visualization. Additionally, they support senior leadership by overseeing the development of business insights, reports, and AI capabilities to inform decision-making processes and drive impactful outcomes.
 
 
 Main Responsibilities
 
 
 <ul>
 <li>
 Shareholder &amp; Financial: - Implement Key Performance Indicators (KPIs) and monitor the performance of Data &amp; AI-driven solutions to measure their impact on business outcomes. - Promote cost consciousness and efficiency in Data Analytics and AI projects to minimize expenses and maximize returns. - Implement Key Risk Indicators (KRIs) and manage the Group&rsquo;s exposure to Data &amp; AI related risk effectively accordingly. - Coordinate and obtain approval from the EVP Data &amp; Analytics for projects and new systems that would impact capital or operating expenditures. - Take part in the overall QNB Data &amp; Analytics strategy execution. - Communicate comprehensive and cost-effective Data, Analytics &amp; AI solutions to user requirements keeping in mind the Group&rsquo;s budgets and targets while enhancing productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent.
 </li>
 <li>
 Customer (Internal &amp; External): - Collaborate closely with peers, key divisional stakeholders, and third-party support teams to identify and implement advanced data-driven and AI solutions that deliver substantial value for QNB and its customers. - Translate complex business needs into comprehensive data science and analytics requirements to support strategic business decision-making. - Provide strategic guidance regarding the potential and implementation of AI and data science within the organization. - Assist customers with thorough and insightful responses to their inquiries about the Bank&rsquo;s products and strive to provide innovative solutions to their requests. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Build and maintain robust and effective relationships with related departments and units to achieve the Group&rsquo;s overarching objectives. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - To assist customers in all their queries on Bank&rsquo;s product and seek solution to their requests. - Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. - Build and maintain strong/effective relationships with related departments/units to achieve the Group&rsquo;s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required.
 </li>
 <li>
 Internal (Processes, Products, Regulatory):
 </li>
 <li>
 Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. - Integrate domain knowledge into AI solutions, such as leveraging financial risk data, customer journey analytics, quality predictions, and sales and marketing data. - Continuously monitor the performance and health of AI-driven models, ensuring high-quality outputs and efficiency. - Establish best practices for AI development and production infrastructure, including cloud computing, Spark, GPU utilization, and containerization. - Design and conduct analytics with the highest standards of model validation, accuracy, encompassing study design, methodology, algorithms, and statistical modelling.
 </li>
 <li>
 Learning &amp; Knowledge: - Ensure a comprehensive understanding of business requirements to deliver the most effective data, analytics, and AI solutions. - Possess detailed knowledge of system architecture and limitations to determine optimal problem-solving methods. - Understand user requirements and existing data structures to provide appropriate solutions by enhancing existing systems or implementing new ones. - Stay updated with methodologies, tools, and industry trends in machine learning, artificial intelligence, and data analytics. - Proactively identify areas for professional development in data science and undertake relevant development activities. - Seek out opportunities to stay current with advancements in AI and data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.
 </li>
 <li>
 Legal, Regulatory, and Risk Framework Responsibilities: - Adhere to all pertinent legal, regulatory, and internal compliance requirements, including but not limited to policies on Data Protection, Fraud Control, and Anti-Money Laundering (AML) &amp; Counter-Terrorist Financing (CTF). - Understand and effectively perform your role within the Three Lines of Defence framework to identify, measure, monitor, manage, and report risks related to data, analytics, and AI projects. - Ensure optimal outcomes for clients in line with Conduct Risk policy by leveraging AI and analytics tools ethically and responsibly. - Support the Risk and Control Self-Assessment (RCSA), Key Risk Indicators (KRI), incident reporting, and remediation processes, as applicable, in accordance with Operational Risk Management guidelines specific to data and AI initiatives. - Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. - Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI.
 </li>
 <li>
 Other: - Ensure high standards of data protection and confidentiality to safeguard all data and systems. - Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. - Maintain high professional standards to uphold the organization's reputation and to strengthen its leadership position in data analytics and AI. - All other ad hoc duties/activities related to data analytics and AI that management might request from time to time
 
 
 </li>
 </ul>
 
 Education And Experience Requirements
 
 
 
 <ul>
 <li>
 University graduate preferably with a Major in computer science, data science, software engineering, information systems, or a related quantitative field.
 </li>
 <li>
 At least 10 years of relevant experience, preferably within a Data Scientist or related role.
 </li>
 <li>
 A PhD in statistics, ML, computer science or the natural sciences, especially physics or any engineering disciplines or equivalent, would be desirable.
 </li>
 <li>
 Candidates must have a specialization in ML, AI, cognitive science, or data science, with extensive hands-on experience in developing data science and AI solutions using machine learning, deep learning, and LLM techniques.
 </li>
 <li>
 Sound knowledge and implementation experience on LLM based solutions.
 </li>
 <li>
 Prior experience in banking is desirable
 </li>
 <li>
 Sound knowledge in cloud technologies ,Python and full stack engineering is must.
 
 
 </li>
 </ul>
 Note: you will be required to attach the following:
 
 
 <ul>
 <li>
 Resume/CV
 </li>
 <li>
 Copy of Passport or QID
 </li>
 <li>
 Copy of Education Certificate
 </li>
 </ul>
</div>

QNB3619 - Assistant Vice President, Data Science

Al Adyat consultancy

Job Profile: AI Expert for Plant Data Model (PDM Project)Job SummaryWe are seeking a highly skilled AI Expert to design, build, and operationalize AI/ML solutions that deliver measurable business outcomes. The ideal candidate combines deep machine learning expertise with strong software engineering practices, MLOps proficiency, and stakeholder collaboration. This role will lead end-to-end projects&mdash;from problem framing and data acquisition to model development, deployment, monitoring, and continuous improvement&mdash;while ensuring compliance with security, privacy, and governance policies.Key Responsibilities&middot; Partner with business stakeholders to translate strategic objectives into AI use cases with clear KPIs and ROI.&middot; Own the full ML lifecycle: data sourcing, feature engineering, model selection, training, evaluation, and production deployment.&middot; Implement robust MLOps: CI/CD for ML, model registry, automated testing, reproducible pipelines, and monitoring (drift, performance, fairness).&middot; Design scalable data/feature pipelines using best practices for data quality, lineage, and governance.&middot; Develop models across domains (e.g., predictive analytics, time series, NLP, computer vision, recommender systems).&middot; Optimize models for efficiency and cost across CPU/GPU, leveraging quantization, distillation, or serving optimizations.&middot; Deploy and maintain models on cloud and on-prem platforms; orchestrate with containers and microservices (Docker/Kubernetes).&middot; Establish and enforce responsible AI practices: privacy-preserving methods, bias detection/mitigation, explainability, and secure handling of data.&middot; Produce high-quality documentation: design docs, runbooks, experiment logs, and user guides; present results to technical and non-technical audiences.&middot; Mentor engineers and analysts; contribute to standards, templates, and reusable components within the AI platform.Minimum Qualifications&middot; Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, or related field (or equivalent experience).&middot; 5+ years building and deploying ML models in production environments.&middot; Strong programming skills in Python and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).&middot; Hands-on experience with data processing frameworks (e.g., Pandas, Spark), SQL/NoSQL databases, and feature stores.&middot; Proficiency in MLOps tooling (e.g., MLflow, DVC, Kubeflow, Airflow) and CI/CD for ML.&middot; Experience deploying to cloud platforms (e.g., Azure Machine Learning, AWS SageMaker, GCP Vertex AI) and container orchestration (Docker/Kubernetes).&middot; Solid understanding of statistics, experiment design (A/B testing), and model validation techniques.&middot; Excellent communication and stakeholder management skills; ability to articulate complex concepts clearly.Preferred Qualifications&middot; Master&rsquo;s or PhD in a quantitative field.&middot; Experience with NLP (transformers, LLMs, RAG) and computer vision (CNNs, detection/segmentation).&middot; Exposure to time-series forecasting, optimization, and reinforcement learning for industrial use cases.&middot; Experience with Azure ecosystem (Azure ML, Databricks, Data Factory, Synapse) and enterprise integration patterns.&middot; Familiarity with privacy-preserving techniques (differential privacy, federated learning) and model interpretability (SHAP, LIME).&middot; Track record of delivering AI solutions in manufacturing, energy, or operations (e.g., predictive maintenance, process optimization).Technical Stack &amp; Tools&middot; Languages: Python (preferred), SQL; familiarity with C++/Java is a plus.&middot; ML/AI: scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face; experiment tracking (MLflow).&middot; Data: Pandas, Spark, Delta/Parquet; data versioning (DVC); feature stores.&middot; Pipelines &amp; Orchestration: Airflow, Prefect, Kubeflow; Docker/Kubernetes for serving.&middot; Monitoring &amp; Observability: Prometheus/Grafana; model drift/performance monitoring tools.&middot; DevOps: Git, GitHub/GitLab, CI/CD, testing frameworks (pytest).&middot; Cloud: Azure (preferred), AWS, GCP; serverless and managed ML services.Core Competencies &amp; Soft Skills&middot; Business acumen with the ability to prioritize use cases based on value and feasibility.&middot; Structured problem solving and hypothesis-driven experimentation.&middot; Clear written and verbal communication, storytelling with data, and visualization skills.&middot; Collaboration and mentorship across cross-functional teams (engineering, operations, compliance).&middot; Ownership mindset with a focus on reliability, safety, and continuous improvement.AI Governance, Security &amp; Compliance&middot; Adhere to corporate data governance policies, security standards, and regulatory requirements (e.g., GDPR where applicable).&middot; Implement role-based access controls, encryption, secure secrets management, and audit trails across the ML stack.&middot; Ensure models meet fairness, transparency, and explainability guidelines; conduct regular risk assessments and reviews.Success Criteria &amp; KPIs&middot; Cycle time from ideation to production (weeks).&middot; Model performance against business KPIs (e.g., accuracy, precision/recall, uplift, cost savings).&middot; Operational reliability (SLA adherence, downtime, incident rate).&middot; Adoption and user satisfaction for AI-enabled products and workflows.Compliance metrics (governance checks passed, audits completed).Job Type: Full-timePay: From QAR15,000.00 per monthEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>AI Expert for Plant Data Model (PDM Project) : 3 years (Required)</li></ul>Language:<ul><li>Arabic (Required)</li><li>English (Required)</li></ul>License/Certification:<ul><li>degree in computer science, Data Science (Required)</li></ul>Location:<ul><li>Doha (Required)</li></ul>

AI Expert for Plant Data Model (PDM Project)

Scale AI

<div>
 Role Overview
 
 
 Scale&rsquo;s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:
 
 
 <ul>
 <li>
 Creating custom AI applications that will impact millions of citizens
 </li>
 <li>
 Generating high-quality training data for national LLMs
 </li>
 <li>
 Upskilling and advisory services to spread the impact of AI
 
 
 </li>
 </ul>
 As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.
 
 
 At Scale, we&rsquo;re not just building AI solutions&mdash;we&rsquo;re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you&rsquo;re ready to shape the future of AI in the public sector and be a founding member of our team, we&rsquo;d love to hear from you.
 
 
 
 You will:
 
 
 
 <ul>
 <li>
 Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
 </li>
 <li>
 Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
 </li>
 <li>
 Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
 </li>
 <li>
 Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
 </li>
 <li>
 Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
 </li>
 <li>
 Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
 </li>
 <li>
 Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.
 
 
 </li>
 </ul>
 
 Ideally, you have:
 
 
 
 <ul>
 <li>
 Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
 </li>
 <li>
 Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
 </li>
 <li>
 System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
 </li>
 <li>
 Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
 </li>
 <li>
 Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
 </li>
 <li>
 Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
 </li>
 <li>
 Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.
 
 
 </li>
 </ul>
 
 
 PLEASE NOTE:
 
 
 
 Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
 
 
 
 
 About Us:
 
 
 
 
 At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
 
 
 
 
 We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
 
 
 
 
 We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's
 
 
 Know Your Rights poster
 
 
 for additional information.
 
 
 
 
 We comply with the United States Department of Labor's
 
 
 Pay Transparency provision
 
 
 .
 
 
 
 
 
 PLEASE NOTE:
 
 We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants&rsquo; needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
 
</div>

AI Applications Ops Lead, GPS

McKinsey & Company

<div><div><div>Job ID: 103368
<div><div><li>Doha</li><li>Riyadh</li></div></div><div> 
</div></div><div> 
 
<div>Do you want to work on complex and pressing challenges&mdash;the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you&rsquo;ve come to the right place.
</div></div><div><div>YOUR IMPACT
<div>As a Software Engineer with Tech &amp; AI at McKinsey, you will work with clients across a wide range of sectors and industries, advising them on how to best leverage technology.</div><div></div><div>
You will drive architectural design, make key technology decisions, and employ agile methodologies to build and deliver the next generation of products for our clients at scale.</div><div></div><div>
You will also lead project workstreams, helping clients build their technical capabilities and foster a culture centered around engineering best practices, user-centricity, and Agile values.</div><div></div><div>
As a core member of the team, you will take on responsibilities that include driving architectural design and making strategic technology decisions to shape next-generation products for various internal teams, ensuring that we remain at the forefront of technological innovation.</div><div></div><div>
Additionally, you will be hands-on and co-creating solutions alongside our clients and their leadership, enabling you to grow into a recognized technology leader.</div><div></div><div>
You will be part of the McKinsey Digital team in Riyadh, Saudi Arabia. This group brings together the best of McKinsey&rsquo;s digital capabilities to help our clients use digital technology to transform their businesses.</div><div></div><div>
McKinsey Digital is our tech delivery people unit. A global team of software, data and cloud engineers, passionate designers, technology architects, product owners, and leading technologists.</div><div></div><div>
You will join a multidisciplinary community of developers, Agile coaches, designers, business strategists and experts. Together, we will design and create industry shaping products and tools for our clients.</div><div></div><div>
While we advocate for using the right tech for the right task, we often leverage the following technologies: JavaScript, TypeScript, React.js, Angular.js, Next.js, Vue.js, Python, Java, C#, NodeJS, SQL, MongoDB, AWS, Azure, GCP, and more!</div><div></div><div>
Our office culture is casual and social, with an emphasis on education and innovation. You will have the freedom to try new ideas and experiment in your role and will be guaranteed significant dedicated time to tinker, create, continuously learn and share cool new stuff. We also have a strong emphasis in our teams on mentoring others enabling them to grow and learn.</div><div></div><div>
Changing the world requires us to sit with our clients at times, so some travel is expected in this role.</div>
</div></div><div><div>YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues&mdash;at all levels&mdash;will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won&rsquo;t find anywhere else.
When you join us, you will have:<div><ul><li>
Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.</li><li>
A voice that matters: From day one, we value your ideas and contributions. You&rsquo;ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.</li><li>
Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm&rsquo;s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you&rsquo;ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.</li><li>
World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.</li></ul></div>
</div></div><div><div>YOUR QUALIFICATIONS AND SKILLS
<div><div><ul><li>Undergraduate or master&rsquo;s degree; or equivalent experience</li><li>
5+ years of experience in software development, with significant full-stack web application development experience strongly preferred</li><li>
Demonstrated knowledge and hands-on experience across the full application stack with some of the following languages/frameworks: JavaScript, TypeScript, React, Angular, Vue, jQuery, Java, Sprint, C#, .NET, Node.js, SQL, MySQL, SQL Server, MongoDB, cloud-native databases, AWS, Azure, GCP, Jenkins, Docker, Circle CI, Travis</li><li>
Experience leading in Agile teams, including coaching and modeling Agile mindsets as part of sprint ceremonies, work definition and building developer capabilities</li><li>
Experience working collaboratively with technical and non-technical team members and stakeholders including modeling and coaching others to use engineering best practices such as design patterns, customer-centric design, test-driven development, code refactoring, code review, and OWASP Top 10 security awareness</li></ul></div></div></div></div></div></div>

Software Engineer II - Tech & AI at McKinsey

Forvis Mazars in Qatar

<div>Job responsibilities: 
<ul><li>Responsible for overall design, operation, maintenance and continuous improvement of the data, analytics and artificial intelligence platforms used by the Security Operations Center (further referenced as SOC). Responsibilities and duties are planned as follows:</li></ul>

<ul><li>Continuous maintenance of the data pipelines, analytics platforms and AI models used by the Security Operations Center; including data ingestion, normalization, feature extraction, model training and deployment.</li></ul>

<ul><li>Ensuring the overall health of the SOC data platform, analytics engines, machine learning models, and AI-assisted detection systems.</li></ul>

<ul><li>Manage verification, validation, tuning, and quality of security telemetry including logs, NetFlow/IPFIX, EDR data, threat intelligence feeds and other SOC data sources.</li></ul>

<ul><li>Develop, train, validate and tune machine learning and analytics models used for:</li></ul>

<ul><li>Anomaly detection</li></ul>

<ul><li>Threat classification</li></ul>

<ul><li>Behavioral analysis</li></ul>

<ul><li>Alert prioritization and risk scoring</li></ul>

<ul><li>Deploy and tune detection models and analytic use cases driven by security intelligence, threat hunting and incident response requirements.</li></ul>

<ul><li>Implement analytic use cases as required by Security Intelligence, Tier-2 and Tier-3 teams.</li></ul>

<ul><li>Manage and coordinate data source onboarding, integration, normalization, enrichment and troubleshooting for all SOC telemetry sources.</li></ul>

<ul><li>Manage access and permissions for data platforms, analytics environments and AI systems used by the SOC.</li></ul>

<ul><li>Ensure that security data sources are correctly feeding the analytics and AI platforms.</li></ul>

<ul><li>Generate analytical reports, dashboards and model outputs as required by SOC management, threat hunting and incident response teams.</li></ul>

<ul><li>Configuration, management, performance tuning and capacity planning of SOC data, analytics and AI platforms.</li></ul>

<ul><li>Support proof-of-concepts (POCs) for new SOC data sources, analytics techniques and AI-driven security capabilities.</li></ul>

<ul><li>Review vendor, open-source and research developments in security analytics, machine learning and AI relevant to SOC operations.</li></ul>

<ul><li>Should have good knowledge of systems, solutions and security tools and skills as follows:</li></ul>

<ul><li>Knowledge of MS Windows and UNIX-based systems.</li></ul>

<ul><li>Knowledge of data engineering and big-data platforms (data pipelines, stream processing, data lakes).</li></ul>

<ul><li>Knowledge of security telemetry including SIEM data models, NetFlow/IPFIX, EDR telemetry and threat intelligence formats.</li></ul>

<ul><li>Knowledge of machine learning and analytics techniques including anomaly detection, classification, clustering and statistical modeling.</li></ul>

<ul><li>Knowledge of AI-driven SOC technologies including LLM-based assistants, automated enrichment and detection analytics.</li></ul>

<ul><li>Familiarity with MITRE ATT&amp;CK, incident response lifecycle and threat hunting methodologies.</li></ul>

<ul><li>Problem-solving skills to identify data quality, detection gaps and model performance issues.</li></ul>

<ul><li>Communication with SOC teams (Tier-1, Tier-2, Tier-3) to align analytics and AI capabilities with operational needs.</li></ul>

<ul><li>Communication with vendors and data providers related to SOC analytics, telemetry and AI platforms.</li></ul>

Required certifications in:

<ul><li>Data engineering, analytics or AI platforms (Cloudera, Databricks, AWS, Azure, GCP, etc.)</li></ul></div>

CSOC Data Analyst L2

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