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malomatia

<div>
 
 Job Description
 
 
 
 To define technical approach to AI agents, orchestration frameworks, and responsible AI practices while working closely with engineering teams, product managers, and business stakeholders to bring cutting-edge AI capabilities to production.
 
 
 
 Responsibilities
 
 
 
 Lead AI solutions design and implementation
 
 
 <ul>
 <li>
 Serve as the primary technical advisor on generative AI initiatives
 </li>
 <li>
 Lead proof-of-concept development and architectural decision records
 </li>
 <li>
 Mentor engineering teams on agentic AI patterns and best practices
 </li>
 <li>
 Evaluate emerging technologies and maintain technical roadmaps
 </li>
 <li>
 Design and architect AI agent systems and multi-agent workflows for enterprise use cases
 </li>
 <li>
 Evaluate and implement agent frameworks including LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, Google Agent-to-Agent (A2A), and emerging standard
 </li>
 <li>
 Architect tool-use patterns, function calling, MCP, and agent-to-agent communication protocols
 </li>
 <li>
 Design for agent observability, debugging, and human-in-the-loop workflows
 </li>
 <li>
 Design retrieval-augmented generation architectures and architect vector database solutions, embedding strategies, implement chunking strategies, hybrid search, and re- ranking approaches for optimal retrieval performance
 </li>
 <li>
 Design knowledge graphs and structured data integration with generative AI systems
 </li>
 <li>
 Lead architecture decisions across cloud AI platforms including Azure AI Foundry, Google Vertex AI, OpenAI APIs, and open-source Gen AI models
 </li>
 <li>
 Design prompt management, versioning, and optimization pipelines
 </li>
 <li>
 Architect for multi-model strategies, model routing, and fallback patterns
 </li>
 <li>
 Establish patterns for cost optimization, latency management, and scaling LLM workloads
 </li>
 <li>
 Define comprehensive evaluation frameworks for LLM applications and agent systems
 </li>
 <li>
 Implement automated evaluation pipelines using frameworks such as RAGAS, DeepEval, and custom evaluation harnesses
 </li>
 <li>
 Establish benchmarks for response quality, factual accuracy, task completion, and user satisfaction
 </li>
 <li>
 Champion responsible AI practices including safety, fairness, transparency, and privacy
 </li>
 <li>
 Implement guardrails, content filtering, and output validation systems
 </li>
 <li>
 Design for prompt injection prevention, data leakage protection, and secure agent execution
 </li>
 <li>
 Ensure compliance with emerging AI regulations and industry standards
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred. Arabic Speaker.
 </li>
 <li>
 8+ years of experience in software engineering or architecture roles
 </li>
 <li>
 3+ years of hands-on experience building LLM-powered applications in production
 </li>
 <li>
 Deep expertise in AI agent architectures, orchestration patterns, and workflow design
 </li>
 <li>
 Strong experience with at least two of the following: LangChain/LangGraph, Microsoft Semantic Kernel/Agent Framework, OpenAI Agents SDK, Google Vertex AI Agent Builder
 </li>
 <li>
 Proven experience designing and implementing Advanced RAG Systems and Agentic AI
 </li>
 <li>
 Proficiency in Python and experience with async programming patterns
 </li>
 <li>
 Hands-on experience with cloud AI platforms (Azure AI Foundry or Google Vertex AI)
 </li>
 <li>
 Strong understanding of Gen AI models&rsquo; fundamentals including prompting, fine-tuning, context windows, and token economics
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience implementing Model Context Protocol (MCP), Google Agent-to-Agent (A2A) protocol, and multi-agent communication patterns
 </li>
 <li>
 Experience building AI Evals pipelines and AI quality assurance systems
 </li>
 <li>
 Knowledge of advanced RAG techniques: query decomposition, multi-hop reasoning, GraphRAG
 </li>
 <li>
 Experience with AI observability tools
 </li>
 <li>
 Background in AI safety, red-teaming, or responsible AI implementation.
 
 
 </li>
 </ul>
 Skills &amp; Competencies
 
 
 <ul>
 <li>
 Systems thinking with ability to design for complexity and emergence in agentic systems
 </li>
 <li>
 Strong communication skills to convey AI concepts to diverse audiences
 </li>
 <li>
 Pragmatic approach balancing innovation with production readiness
 </li>
 <li>
 Ability to rapidly learn evolving AI technologies
 </li>
 <li>
 Commitment to ethical AI development and user safety
 </li>
 <li>
 Collaborative mindset with ability to influence across organizational boundaries
 
 
 </li>
 </ul>
 
 About Malomatia
 
 
 
 
 ABOUT US
 
 
 
 malomatia is a leading Qatar-based IT services and solutions provider, bringing together top Qatari and international talent to deliver innovative, end-to-end technology solutions that empower clients to achieve their strategic goals.
 
 
 
 Our mission
 
 
 
 Empowering Qatar&rsquo;s businesses and governments to leap into the digital future with agile, knowledge-driven solutions.
 
 
 
 Our vision
 
 
 
 To become Qatar&rsquo;s trusted knowledge partner in digital transformation, disrupting industries, shaping the future, and building a world-class tech ecosystem.
 
 
 
 Driving change that makes a real impact
 
 
 
 Since 2008, malomatia has been driving Qatar&rsquo;s digital transformation through innovative, ISO-certified IT solutions. With expertise across key public and private sectors, we empower the nation&rsquo;s vision with advanced services in cloud, cybersecurity, AI, and contact center excellence, elevating the role of technology in shaping Qatar&rsquo;s sustainable future.
 
 
 
 About The Team
 
 
 
 Established in 2008, malomatia is a Qatari leader in IT services and digital transformation. We serve key sectors including Government, Healthcare, Education, Customs, and Transportation, delivering impactful solutions that support national development goals. Powered by a diverse team of skilled Qatari and international IT professionals, we deliver innovative, high-value digital solutions tailored to the unique needs of our clients.
 
 
 Our mission is to inspire customers to thrive through digital excellence, and we envision becoming the trusted partner of choice in building a smarter society through technology and talent. We are driven by core values that define our culture and approach: ownership, integrity, empathy, teamwork, transparency, agility, excellence, trust, and innovation.
 
 
 Join us in shaping the future of technology in Qatar
</div>

Senior Consultant - AI Solution Architect

Confidential

<h2>Job Summary</h2>The Help Desk &amp; CAFM System Coordinator will coordinate service requests and work orders across a large-scale electromechanical maintenance and Facility Management project, ensuring effective Help Desk operations and accurate use of the CAFM system.<h2>Key Responsibilities</h2><ul><li>Manage daily FM Help Desk operations.</li><li>Receive, log, categorize, assign, and monitor maintenance requests.</li><li>Maintain accurate work-order information within the CAFM system.</li><li>Coordinate with customers, engineers, supervisors, and technicians.</li><li>Monitor outstanding work orders and support timely completion.</li><li>Train users on CAFM functionality and established workflows.</li><li>Monitor compliance with Help Desk and CAFM procedures.</li><li>Prepare operational and performance reports.</li><li>Analyze service issues and support fast and effective resolution.</li></ul><h2>Requirements</h2><ul><li>Higher education degree.</li><li>Minimum 2 years' experience in Help Desk operations or Customer Service within FM or a related environment.</li><li>Previous supervisory-level experience.</li><li>Experience using electronic work-management systems.</li><li>CAFM experience strongly preferred.</li><li>Good understanding of technical and non-technical FM services.</li><li>Strong Microsoft Office skills.</li><li>Fluent in Arabic and English, spoken and written.</li><li>GCC experience preferred.</li></ul>

Help Desk & CAFM System Coordinator

<h2>Job Summary</h2>The Help Desk &amp; CAFM System Coordinator will coordinate FM help desk activities and CAFM operations, ensuring service requests are accurately logged, assigned, monitored, escalated, and closed within agreed service levels.<h2>Key Responsibilities</h2><ul><li>Manage daily FM Help Desk and CAFM activities.</li><li>Receive, record, categorize, and assign service requests and work orders.</li><li>Monitor work orders against agreed SLAs and escalate overdue activities.</li><li>Coordinate with technicians, engineers, supervisors, customers, and service providers.</li><li>Maintain accurate CAFM records, reports, and performance information.</li><li>Support and train users on CAFM processes and system functionality.</li><li>Monitor compliance with established help desk procedures.</li><li>Prepare reports on work orders, response times, completion rates, and service performance.</li></ul><h2>Requirements</h2><ul><li>Higher education degree.</li><li>Minimum 2 years' experience in FM Help Desk, Customer Service, CAFM, or a related environment.</li><li>Previous experience operating electronic work management systems.</li><li>Practical experience using a CAFM system is strongly preferred.</li><li>Good understanding of hard and soft FM services.</li><li>Fluent in Arabic and English – mandatory.</li><li>Strong Microsoft Office skills.</li><li>Excellent communication, coordination, organization, and problem-solving capabilities.</li><li>Previous GCC/FM experience is preferred.</li></ul>

Mindstream

Mind Stream is seeking a skilled Data Scientist to join our growing team. You will play a key role in developing, productionizing, and scaling advanced AI solutions, ranging from agentic workflows to time-series forecasting models.Responsibilities:- Design and deploy GenAI solutions using LLMs, RAG, and vector databases.- Build multi-agent AI applications using LangGraph, LangChain, CrewAI, and AutoGen.- Develop and deploy time-series forecasting and anomaly detection models.- Productionize ML models using Python, FastAPI, MLflow, Docker, and Kubernetes.- Collaborate on cloud infrastructure for model deployment and scaling.- Implement and maintain MLOps practices for end-to-end model lifecycle management.Requirements:- Strong programming skills in Python and experience with FastAPI.- Experience with GenAI technologies, prompt engineering, and embeddings.- Familiarity with agentic frameworks and multi-agent workflows.- Hands-on experience with Docker, Kubernetes, and CI/CD pipelines.- Knowledge of cloud platforms and MLOps practices.Experience: 6-14 yearsLocation: Dhahran, Saudi ArabiaApply through Mind Stream Email Id: careers@mind-stream.net WhatsApp: +974 30107270Pay: QAR23,000.00 - QAR27,000.00 per monthWork Location: In person

Data Scientist

North Oil Company Qatar

<div>
 Job description:
 
 
 
 Key Accountabilities
 
 
 &nbsp;
 
 
 
 This will be a definite term contract for 3 years.
 
 
 
 &nbsp;
 
 
 
 Evaluate, test, design and enable technology selection and implementation approach to improvement and optimize&nbsp; capabilities and data architecture (including AI &amp; ML) and design of agentic and autonomous AI solutions for enterprise&nbsp; use cases (covering POC, scale-up, and production&nbsp; deployment)
 
 
 <ul>
 <li>
 Evaluate, test, and design end to end data and AI architectures for enterprise and agentic use cases, covering POC, scale up, and production deployment.
 </li>
 <li>
 Architect enterprise data platforms optimized for AI, ML, and LLM integration and inference at scale.
 </li>
 <li>
 Define AI ready data architecture patterns supporting&nbsp; fine tuning, retrieval augmented generation, and prompt engineering workflows.
 </li>
 <li>
 Design hybrid architectures integrating on premises&nbsp; and cloud based LLM services with enterprise data platforms.
 </li>
 <li>
 Define reference patterns for multi model AI&nbsp; environments operating on shared and governed data.&nbsp;
 </li>
 <li>
 Design semantic layers, indexing, and similarity search for low latency AI workloads.
 </li>
 <li>
 Design enterprise knowledge graph architectures to&nbsp; support reasoning and contextual understanding.
 </li>
 <li>
 Define architectural mechanisms for data refresh,&nbsp; accuracy, relevance, and observability of retrieval performance and latency.
 </li>
 <li>
 Design multi agent architectures for cross functional workflows, including decision logic, tool usage, and&nbsp; interaction patterns for autonomous agents such as&nbsp; &nbsp;Microsoft Fabric Data Agent and Operational Agent.
 </li>
 <li>
 Design guardrails, auditability, and control mechanisms for agent actions, including feedback loops for continuous improvement.
 </li>
 <li>
 Define prompt orchestration patterns for multi-step&nbsp; reasoning aligned with NOC standards.
 </li>
 <li>
 Assess AI models, platforms, and tools using defined evaluation criteria and benchmarking, including proprietary, commercial, and open source options.
 </li>
 <li>
 Review and provide guidance on AI, ML, and advanced analytics architecture artefacts from vendors.
 </li>
 </ul>
 
 Job Purpose
 
 
 Responsible for designing and advancing data solutions that strengthen NOC data architecture and evaluating the adoption of emerging technologies within DBS, with a focus on AI, machine learning, and advanced analytics. The role requires deep expertise in Data &amp; AI Architecture /Engineering, cloud platforms,&nbsp;and integration patterns, combined with strong Oil &amp; Gas domain knowledge. It aims to enhance enterprise analytics capabilities by integrating AI/ML models and large-scale data processing frameworks to enable data-driven decision-making and improve operational efficiency.&nbsp;
 
 
 Key Accountabilities:
 
 <ul>
 <li>
 Evaluate, test, design and enable technology selection and implementation approach to improvement and optimize capabilities and data architecture (including AI &amp; ML) and design of agentic and autonomous AI solutions for enterprise use cases (covering POC, scale-up, and production deployment)
 </li>
 <li>
 Provide architectural guidance for data integration, ingestion patterns across enterprise data platforms and advanced analytics solutions in alignment with data modelling and MDM standards
 </li>
 <li>
 Design solutions in alignment with DBS best practices&nbsp; on Data and AI governance, information security controls, EA and PMO standards
 </li>
 <li>
 Review solutions and demands impacting Data Management part of Architecture Review Board (ARB)
 
 meetings
 </li>
 </ul>
 
 Key Accountabilities
 
 
 
 Provide architectural guidance for data integration, ingestion patterns across enterprise data
 
 
 platforms and advanced analytics solutions in alignment with data modelling and MDM standards
 
 
 <ul>
 <li>
 &nbsp;Design batch and streaming or real time ingestion and integration patterns aligned with NOC standards,&nbsp;
 
 including Integration Design Documents and design first principles.
 </li>
 <li>
 Define medallion, Kappa, and Lambda architectures as reference patterns.
 </li>
 <li>
 Maintain NOC data architecture for data platforms,&nbsp; digital use cases, demands, and data solutions.&nbsp;
 </li>
 <li>
 Document reference architectures and standard&nbsp; solution patterns for data and AI solutions, including&nbsp; IDD, HLD, LLD, dashboards and reports, model representations, data dictionaries, and data models&nbsp; such as CDM,LDM, and PDM.&nbsp;
 </li>
 <li>
 Ensure alignment of MDM principles with analytics and AI data requirements.
 </li>
 <li>
 Design data pipelines supporting continuous model training, evaluation, deployment, and retraining.
 </li>
 <li>
 Design CI and CD flows for ML models with monitoring for accuracy, latency, and cost.
 </li>
 <li>
 Design cost efficient inference and fine-tuning&nbsp; pproaches with usage tracking and controls..
 </li>
 </ul>
 
 
 Design solutions in alignment with DBS best practices on Data and AI governance, information security controls, EA and PMO standards
 
 
 <ul>
 <li>
 Support alignment with data and AI governance to ensure trusted and well governed data usage across&nbsp;
 
 platforms and advanced analytics.
 </li>
 <li>
 Design privacy preserving architectures for model&nbsp; training and fine tuning.
 </li>
 <li>
 Support definition of security controls and access patterns for data and AI platforms.
 </li>
 </ul>
 
 
 Review solutions and demands impacting Data Management part of Architecture Review Board (ARB) meetings
 
 
 <ul>
 <li>
 &nbsp;Support Architecture Review Board and Design Advisory sessions for data, AI, and ML solution reviews and approvals.
 </li>
 <li>
 Support delivery teams through architecture reviews and structured feedback on design artefacts.
 </li>
 <li>
 Identify and review reference solutions, architectures, and case studies to improve NOC architecture.
 </li>
 <li>
 Provide technical guidance to data operations, data governance, and related teams as required.
 </li>
 </ul>
 Competencies Delegate Appropriately and Communicate Effectively Demonstrate Adaptability in Managing Complex Situations Demonstrate Learning Agility and Drive Innovation Develop Emotional Intelligence and Cultural Competence Develop Others and Institutionalise Knowledge Develop Talent for the Future NOC Sustainability Facilitate Collaboration and Sense of Community Improve Safety, Technical Proficiency and Results Lead By Example with NOC Values Set Purpose, Strategic Direction and Company Plan Strengthen Accountability and Continuous Improvement Think and Act in Stakeholder-Centric Ways
 
 Education
 
 
 &nbsp;
 
 <ul>
 <li>
 Bachelor of Computer Science or Computer Engineering or relevant degree
 </li>
 <li>
 Specialization and certification in AI, ML engineering and/or Data Science.
 </li>
 </ul>
 
 Experience
 
 
 &nbsp;
 
 <ul>
 <li>
 Minimum of 8 years relevant experience in technical implementation of AI solutions. Designing data architectures, developing AI models, and ensuring the technical robustness of AI systems.
 </li>
 <li>
 Experience with machine learning techniques, such as Supervised/Unsupervised Learning, Deep Learning (e.g., Neural Networks, CNNs, RNNs), Natural Language&nbsp; Processing (NLP), Computer Vision and Text Analytics
 </li>
 <li>
 Hands on Experience with data agents, operational agent and Agentic AI
 </li>
 <li>
 Proven track record of delivering successful AI /Data digital products in the industry.
 </li>
 </ul>
 
 
 Job-Specific Skills (Generic / Technical):
 
 
 <ul>
 <li>
 Experience in AI Ready Data platforms &amp; Data architecture and data engineering foundation, technical
 
 implementation of AI solutions. Designing data&nbsp; architectures, developing AI models, and ensuring the
 
 technical robustness of AI systems.
 </li>
 <li>
 Strong understanding of software development life cycle (SDLC) and DevOps Practices.
 </li>
 <li>
 Strong hands-on Experience in AI and ML architecture, including Agentic and autonomous AI &amp; ML Ops Life cycle includes running POC to scale up solutions&nbsp;
 </li>
 <li>
 Strong Experience of design pipelines for model&nbsp; training, evaluation, and retraining including CI/CDD
 </li>
 <li>
 Excellent problem-solving skills and attention to detail.
 </li>
 <li>
 Strong communication and teamwork abilities.
 </li>
 <li>
 Ability to work independently.
 </li>
 <li>
 Experience with agile tools and software, such as Jira, Confluence, or similar.
 </li>
 <li>
 Experience on Projects using Industry Data Platforms (such as OSDU or Cognite Date Fusion) would be a plus
 </li>
 </ul>
</div>

Data Architect

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
 
 
 
 <ul>
 <li>
 The Senior AI Engineer is responsible for leading the design, development, and deployment of complex Agentic AI solutions and enterprise AI platforms within the Data &amp; AI Lab. This senior role requires deep expertise in AI engineering, cloud architecture, and integration patterns, combined with financial services industry experience.
 </li>
 <li>
 The position serves as a technical leader for AI initiatives, providing guidance on architecture decisions, best practices, and technology selection. The Senior AI Engineer will drive the adoption of AI orchestration frameworks (MCP), cloud-native AI services, and modern AI tooling across the organization.
 </li>
 <li>
 The role requires a balance of hands-on technical delivery and technical leadership, ensuring that AI solutions are production-grade, scalable, and aligned with banking regulatory requirements.
 
 
 </li>
 </ul>
 
 
 Key Accountabilities
 
 
 
 
 <ul>
 <li>
 Agentic AI Architecture &amp; Development
 </li>
 <li>
 Lead the design and implementation of complex Agentic AI solutions including autonomous workflows, multi-agent systems, and enterprise AI orchestration.
 </li>
 <li>
 Define architecture patterns and best practices for AI agent development and Model Context Protocol (MCP) integrations.
 </li>
 <li>
 Drive innovation in AI capabilities, evaluating emerging technologies and recommending adoption strategies.
 </li>
 <li>
 AI Platform Leadership
 </li>
 <li>
 Architect and oversee development of AI platform components including vector stores, embedding pipelines, and retrieval systems.
 </li>
 <li>
 Design scalable document parsing, processing, and metadata extraction frameworks for enterprise knowledge management.
 </li>
 <li>
 Define API standards and integration patterns for AI services consumption across the bank.
 </li>
 <li>
 Cloud Architecture &amp; Infrastructure
 </li>
 <li>
 Lead cloud architecture for AI solutions on Azure and GCP, ensuring scalability, security, and cost optimization.
 </li>
 <li>
 Design event-driven architectures using Kafka for real-time AI applications and streaming use cases.
 </li>
 <li>
 Establish infrastructure standards for model serving on OpenShift/Kubernetes, monitoring, and MLOps practices.
 </li>
 <li>
 Technical Leadership
 </li>
 <li>
 Provide technical mentorship to AI Engineers and contribute to team capability building.
 </li>
 <li>
 Lead technical design reviews, code reviews, and architecture discussions.
 </li>
 <li>
 Ensure adherence to best practices: CI/CD, code management, testing, knowledge management, and documentation.
 </li>
 <li>
 Collaborate with enterprise architecture and IT teams to ensure AI solutions align with bank-wide technology strategy and target data architecture.
 </li>
 <li>
 Stakeholder Engagement
 </li>
 <li>
 Partner with AI Product Owners and business stakeholders to translate requirements into technical solutions.
 </li>
 <li>
 Communicate technical concepts and trade-offs to senior management and steering committees.
 </li>
 <li>
 Contribute to AI governance, ensuring solutions comply with data policies, ethical standards, and regulatory requirements.
 </li>
 <li>
 Define and maintain SLAs for AI solutions, implementing necessary monitoring and alerting.
 
 
 </li>
 </ul>
 
 Key Competencies
 
 
 
 <ul>
 <li>
 AI &amp; ML Engineering
 </li>
 <li>
 Deep expertise in LLMs, embedding models, and generative AI architectures.
 </li>
 <li>
 Advanced experience with AI orchestration frameworks, complex agent development, and multi-agent systems.
 </li>
 <li>
 Expert knowledge of vector databases, RAG architectures, and knowledge retrieval patterns.
 </li>
 <li>
 Strong background in deep learning frameworks (TensorFlow, PyTorch) and model deployment tools (MLflow, TFX).
 </li>
 <li>
 End-to-end ML lifecycle management and model monitoring.
 </li>
 <li>
 Software Engineering
 </li>
 <li>
 Expert proficiency in Python (Advanced level) and AI/ML frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar).
 </li>
 <li>
 Strong experience with API design, microservices architecture, and event-driven architecture.
 </li>
 <li>
 SQL &ndash; Advanced user (Stored Procedures, Window functions, Temp Tables, Recursive Queries).
 </li>
 <li>
 Git (GitHub/GitLab), CI/CD pipelines, and code management best practices.
 </li>
 <li>
 Cloud &amp; Data Engineering
 </li>
 <li>
 Expert-level experience with cloud platforms (Azure and/or GCP) and object storage (S3, GCS, ABS).
 </li>
 <li>
 Advanced knowledge of Kafka, Spark, and workflow orchestration (Airflow, Apache NiFi).
 </li>
 <li>
 Expert in containerization and orchestration: Docker, K8s (OpenShift).
 </li>
 <li>
 MLOps practices including model monitoring, versioning, and management.
 </li>
 <li>
 Leadership &amp; Communication
 </li>
 <li>
 Proven ability to lead technical initiatives and mentor junior engineers.
 </li>
 <li>
 Strong stakeholder management and communication skills.
 </li>
 <li>
 Data visualization and reporting for executive communication.
 </li>
 <li>
 Experience collaborating across organizational boundaries with IT, security, and compliance teams.
 
 
 </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>
 7+ years of experience in software engineering with at least 4 years focused on AI/ML applications.
 </li>
 <li>
 Demonstrated experience leading technical delivery of AI solutions in production environments.
 </li>
 <li>
 Expert-level experience with cloud platforms (Azure or GCP), OpenShift/Kubernetes, and enterprise integration patterns.
 </li>
 <li>
 Banking or financial services industry experience is mandatory.
 </li>
 <li>
 Experience with regulatory compliance, data governance, and security in financial services preferred.
 </li>
 <li>
 Relevant certifications (Azure AI Engineer, GCP ML Engineer, or equivalent) strongly 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>

Senior AI Engineer

Scale AI

<div>
 Scale&rsquo;s mission is to develop reliable AI systems for the world's most important decisions. 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>
 Scale is hiring ML Research Engineers to bridge the gap between emerging AI capabilities and mission-critical, real-world impact. In our Global Public Sector (GPS) division, we don&rsquo;t just implement tools; we conduct applied research to solve the unique challenges of sovereign AI.
 
 
 Your role is to move beyond off-the-shelf implementations. You will lead the research into Agent Design, Reliability, and AI Safety, developing novel system architectures that power high-stakes government applications. You will be the bridge between a research paper and a production-ready system that functions at scale.
 
 
 
 The Mission
 
 
 
 <ul>
 <li>
 Applied Agent Research: Leading the design of reliable, multi-step agentic systems and long-horizon reasoning frameworks that can solve complex problems for national security and public policy.
 </li>
 <li>
 Systemic Evaluation &amp; Red-Teaming: Developing rigorous benchmarks and evaluation protocols to ensure AI systems are safe, unbiased, and performant in high-stakes, non-commercial environments.
 </li>
 <li>
 Model Optimisation &amp; Selection: Conducting deep-dive research into model performance (both open-weight and closed) to identify the best tools for niche domains, optimising them through context engineering, RAG, and other inference-time techniques.
 
 
 </li>
 </ul>
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Architect Agentic Systems: Design and build agent architectures, the harnesses, tool-use protocols, and logic flows that allow LLMs to function as reliable, autonomous agents in complex workflows.
 </li>
 <li>
 Drive Reliability &amp; Safety: Research and implement robust evaluation frameworks. This includes red-teaming for sovereign AI requirements and developing strategies to mitigate hallucinations in regulated data environments.
 </li>
 <li>
 Synthesise Deep Research: Build agents capable of autonomous information synthesis and long-horizon reasoning, enabling users to analyse massive datasets and extract actionable insights.
 </li>
 <li>
 Optimize for Niche Domains: Evaluate and adapt models for specialised use cases, such as LLM reasoning for low-resource languages, complex OCR tasks, or working in GPU-constrained environments
 </li>
 <li>
 Build Evaluation Frontiers: Create new, automated benchmarks that define what success looks like for AI in the public sector, ensuring our systems meet the highest standards of accuracy and sovereignty.
 </li>
 <li>
 Consult as a Technical Authority: Act as a subject matter expert for public sector leaders, advising on the practical limits, safety requirements, and performance trade-offs of emerging AI technologies.
 
 
 </li>
 </ul>
 
 Ideally, You Have
 
 
 
 <ul>
 <li>
 Engineering Rigour: Exceptional proficiency in Python and experience building agentic harnesses or AI infrastructure. You write production-ready code that is modular, scalable, and reliable.
 </li>
 <li>
 Applied Research Mindset: A track record of taking theoretical AI concepts and turning them into functional prototypes or products. You know how to read a paper and determine if its methods are actually viable for a production system.
 </li>
 <li>
 Evaluation Expertise: Experience in LLM benchmarking, red-teaming, or building evaluations that go beyond standard academic datasets.
 </li>
 <li>
 Advanced Degree: A Master&rsquo;s or PhD in Computer Science, Mathematics, or a related field (with a focus on ML) is preferred, but we value demonstrated impact and engineering excellence.
 
 
 </li>
 </ul>
 
 Nice to Haves
 
 
 
 <ul>
 <li>
 Agentic Systems Expert: Deep experience in building multi-agent systems, including chain-of-thought optimisation and tool-calling reliability.
 </li>
 <li>
 Sovereign AI Experience: Experience working with highly regulated data environments, on-premise deployments, or sensitive government use cases.
 </li>
 <li>
 Inference Optimisation: Knowledge of how to optimise model performance for environments with limited GPU capacity or specific latency requirements.
 </li>
 <li>
 Zero-to-One Mindset: You are comfortable navigating ambiguity and enjoy defining research directions from scratch to solve a specific product or mission need.
 
 
 </li>
 </ul>
 
 For those applying based in Qatar: Residency and employment in Qatar requires certain permissions (visa and permits) issued by the Qatari authorities. As part of the application process, candidates will be asked to provide personal information, including residency status and nationality, which is required for visa processing. This information is collected solely for immigration compliance purposes and will be not used as a criterion in any hiring decision unless such use is lawfully permitted.
 
 
 Visa issuance is at the discretion of the Qatari authorities. If you are successful in your application, you will be required to provide the documentation requested by Scale and the authorities to obtain the necessary permissions for you to live and work in Qatar, and Scale will work with successful candidates to support the visa application process.
 
 
 
 
 
 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,
 
 
 Ernst
 
 
 &amp;
 
 
 Young, 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>

Machine Learning Engineer, Global Public Sector

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