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Devoteam

<div>
 
 Tech for People Unlocks the Future
 
 
 
 At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
 
 
 With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.
 
 
 
 Devoteam Culture &amp; Values:
 
 
 
 True innovation is born from a powerful culture, fused with meaningful values.
 
 
 
 Culture:
 
 
 
 
 Fair and courageous
 
 
 
 Everyone is treated fairly &ndash; this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
 
 
 
 Ambition and results
 
 
 
 Ambition is nurtured at every step &ndash; this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
 
 
 
 Learning and innovating
 
 
 
 Curiosity and learning are at our core &ndash; this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
 
 
 
 Caring and sharing
 
 
 
 A caring attitude is infused into our culture &ndash; this encourages sharing. We believe in the power of teams, we promote support and collaboration.
 
 
 At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers,
 
 
 
 Values:
 
 
 
 <ul>
 <li>
 Respect
 </li>
 <li>
 Frankness
 </li>
 <li>
 Passion
 
 
 
 </li>
 </ul>
 
 Job Description
 
 
 
 A Data Engineer is expected to develop, monitor, and optimize data quality rules and processes to ensure reliable and accurate enterprise data.
 
 
 They identify and resolve data anomalies through profiling, cleansing, and validation workflows.
 
 
 The role ensures that business decisions are driven by complete, consistent, and high-integrity data across systems.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
 </li>
 <li>
 Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
 </li>
 <li>
 Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
 </li>
 <li>
 Develop automated data quality checks and workflows for continuous monitoring and remediation.
 </li>
 <li>
 Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
 </li>
 <li>
 Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
 </li>
 <li>
 Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
 </li>
 <li>
 Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
 </li>
 <li>
 Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
 </li>
 <li>
 Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
 </li>
 <li>
 Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
 </li>
 <li>
 Conduct root cause analysis and lead remediation programs for chronic data issues.
 </li>
 <li>
 Mentor junior engineers and promote data quality best practices across teams.
 </li>
 <li>
 Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
 </li>
 <li>
 Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
 </li>
 <li>
 Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
 </li>
 <li>
 Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data infrastructure.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Management, or related discipline.
 </li>
 <li>
 5+ years of experience in Data Quality, Data Governance, or Data Engineering roles.
 </li>
 <li>
 Proven hands-on experience with enterprise DQ tools (e.g., Informatica DQ/IDMC, Ataccama, Talend DQ, SAS DQ).
 </li>
 <li>
 Strong expertise in data profiling, rule design, standardization, and exception management.
 </li>
 <li>
 Proficiency in SQL and scripting (Python, Shell, or Scala) for advanced data validation.
 </li>
 <li>
 Deep understanding of data governance frameworks and collaboration with data stewards.
 </li>
 <li>
 Ability to design DQ dashboards, scorecards, and KPIs to monitor performance.
 </li>
 <li>
 Strong communication skills for presenting findings and recommendations to business stakeholders.
 </li>
 <li>
 Experience mentoring junior engineers or managing small DQ workstreams.
 </li>
 <li>
 CDMP Associate Certificate and/or Informatica IDQ Certificate and/or IDMC DQ Certificate
 </li>
 <li>
 Experience defining data quality strategy and embedding DQ into enterprise data platforms (MDM, DWH, Data Lake).
 </li>
 <li>
 Understanding of data lineage, root cause analysis, and impact assessment.
 </li>
 <li>
 Knowledge of metadata management and integration with data catalogs.
 </li>
 <li>
 Familiarity with regulatory and compliance requirements (e.g., NDMO, NDI).
 </li>
 <li>
 Ability to automate DQ workflows through orchestration or CI/CD pipelines.
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 Business Unit: Data &amp; Intelligence
 
 
 
 
 Level: Mid - Senior Level
 
</div>

Data Engineer

Bouygues Construction

<div></div><div><div><div><div>Bouygues Travaux Publics KSA
 
Specialists in civil engineering, underground tuneling and complex structures, delivering major infrastructure and land-use projects worldwide. As part of Bouygues Travaux Publics, we are committed to sustainable construction, diversity, and welcoming talent from all backgrounds. 
 
Job Description 
Design Data Review &amp; Extraction
<ul><li>Review rock excavation design packages (WSP) as they arrive sequentially for data completeness, geometry, volumes, ground support specifications</li>
<li>Review architectural model: C-line / E-line comparison with pricing model</li>
<li>Review RIBA Stage 4 building design: BIM model data integrity and completeness across all disciplines (Solibri)</li>
<li>Extract Material Take-Off (MTO): excavation geometry, volumes, ground supports, rockbolts, steelsets, architectural and MEP quantities</li>
<li>Identify data inconsistencies, clashes, and design coordination issues</li>
<li>Report findings to Technical Director; escalate critical design issues for resolution</li>
<li>Record extracted data completeness status and assumptions for Technical Director approval before workpackages tender / procurement / construction.</li> 
</ul>Model Development &amp; Quantities Management
<ul><li>Develop and maintain integrated design model (3D + data) incorporating design packages as they arrive</li>
<li>Code model elements with design completion status: 30%, 50%, 80%, 100%. Re-baseline quantities at each design stage (30%, 50%, 80%, 100% completion)</li>
<li>Embed quantities data into model for input to cost baseline and supply chain</li>
<li>Track quantities variances as design packages are updated</li>
<li>Provide quantities to Estimating / Finance team for cost+ baseline preparation</li>
<li>Provide excavation material quantities (rockbolts, steelsets) to Operations/Procurement for Purchase Requisition validation; flag variances for PR amendment review</li> 
</ul>Excavation critical Assumptions &amp; Design Basis
<ul><li>Provide input to &quot;critical assumptions&quot; matrix for design section (IFC design inputs)</li>
<li>Document design assumptions: geotechnical basis, ground conditions, structural approach, material standards, ground support specifications</li>
<li>Report assumptions to Technical Director; flag high-risk or uncertain items for review</li> 
</ul>Building Workpackaging &amp; Planning Support
<ul><li>Provide extracted design data (scopes, quantities, specifications, assumptions) to Building technical &amp; construction teams</li>
<li>Support work-package scope definition with detailed design information</li>
<li>Identify design-driven interfaces, handover points, and trade sequencing requirements</li>
<li>Model nodes/interfaces in 4D; support team with defining trade access and phasing sequence</li>
<li>Prepare visualization renderings and 4D construction sequence animations</li> 
</ul>Design Coordination &amp; Change Management
<ul><li>Support development of Design Coordination Procedure: define interface detection, clash resolution, change control, coordination standards</li>
<li>Maintain model versioning following design revisions, RFIs</li>
<li>Extract updated quantities from design package revisions; analyze and report impacts (excavation, ground supports, structural, MEP)</li>
<li>Provide design data to Field Change Request (FCR) and Design Change Process</li>
<li>Escalate unresolved design coordination issues to Technical Director</li> 
</ul>As-Built Data &amp; Field Verification
<ul><li>Coordinate as-built survey data and geometric verification against design</li>
<li>Compare as-built quantities (excavation volumes, ground supports, elements) against contract and design values
</li><li>Track as-built ground conditions vs. design assumptions (geological face mapping, Permit To Tunnel (PTT) documentation)</li>
<li>Update design models with as-built information and document discrepancies</li>
<li>Support Remedial Work (RW) approval with design-reality gap analysis</li>
<li>Monitor trade sequence execution against plan; update 4D model and renderings to reflect actual vs. planned progress</li> 
</ul><div><div>Requirements 
</div></div><div>Qualifications:
<ul><li>Bachelor&rsquo;s degree in engineering</li> 
</ul>Experience:
<ul><li>Experience in BIM, design management, or digital engineering on major projects</li>
<li>Track record in BIM data review</li>
<li>Experience with as-built data capture and geometric verification</li>
<li>Understanding of rock excavation design and RIBA building design stages</li>
<li>Experience preparing 4D models and construction sequence visualizations</li> 
</ul>Personal skills:
<ul><li>Detail-oriented with strong analytical capabilities</li>
<li>Excellent written and verbal communication with technical and executive stakeholders
</li><li>Ability to translate complex design and data issues into clear reports</li>
<li>Proven ability to manage multiple workstreams under time pressure</li>
<li>Collaborative mindset with ability to work across disciplines</li>
<li>Integrity and accountability in data management and reporting</li> 
</ul>Technical Skills:
<ul><li>Advanced BIM proficiency: Revit, Navisworks, Solibri</li>
<li>BIM data review, clash detection, and design coordination</li>
<li>Quantities extraction and bill of materials (MTO)</li>
<li>4D modelling and schedule integration</li>
<li>Data analysis (Excel/PBI)</li>
<li>3D visualization and construction sequence rendering</li>
<li>Survey data integration and geometric verification</li>
<li>Understanding of structural, MEP, and groundworks design</li> 
</ul></div> 
If you have any question feel free to contact Hasna AIT FARES</div></div></div></div>

Project Data Senior Engineer

Maaden

<div>
 
 Job Purpose
 
 
 
 
 JOB DESCRIPTION
 
 
 
 The Principal Specialist, Engineering and ETL (OT) provides enterprise leadership for OT data engineering, enabling reliable ingestion, transformation, and availability of operational data for analytics, operations, and performance management. The role defines OT pipeline standards and assures that OT data is delivered with quality, lineage, security, and appropriate latency across sites.
 
 
 This position is responsible for defining scalable patterns for integrating historians and industrial systems into enterprise platforms, guiding teams through complex OT constraints, and ensuring operational data products are sustainable and governed.
 
 
 
 Key Accountabilities
 
 
 
 <ul>
 <li>
 Define OT data engineering and ETL standards, patterns, and reference architectures covering batch, streaming, and near-real-time ingestion needs.
 </li>
 <li>
 Establish ingestion patterns for historians and OT source systems, including normalization, unit standardization, quality flags, and tag mapping processes.
 </li>
 <li>
 Design and assure robust pipeline reliability (idempotency, backfill, late-arriving data handling, reconciliation, alerting) appropriate for OT contexts.
 </li>
 <li>
 Ensure OT pipelines comply with security and segmentation requirements; partner with OT cyber and platform security teams for governance-by-design.
 </li>
 <li>
 Oversee and guide OT data transformation logic to produce curated OT data products aligned to enterprise models and governance requirements.
 </li>
 <li>
 Provide architectural oversight for site onboarding, handling variability across plants and ensuring consistent delivery standards across implementations.
 </li>
 <li>
 Review and assure vendor and internal deliverables; provide technical direction and quality gates for complex OT engineering initiatives.
 </li>
 <li>
 Drive continuous improvement through performance tuning, cost optimization, observability, and operational resilience improvements for OT workloads.
 
 
 </li>
 </ul>
 
 Minimum Qualification, Experience And Competencies
 
 
 
 
 Minimum Qualification
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science/Engineering, Data Engineering, Industrial Engineering, or related field.
 </li>
 <li>
 Master&rsquo;s degree preferred; OT systems exposure is an advantage.
 
 
 </li>
 </ul>
 
 Minimum Experience
 
 
 
 <ul>
 <li>
 10&ndash;15 years of experience in data engineering/ETL with demonstrated exposure to OT/industrial data environments.
 </li>
 <li>
 Experience designing ingestion from historians/OT systems and delivering analytics-ready OT datasets at enterprise scale.
 
 
 </li>
 </ul>
 
 Skills
 
 
 
 <ul>
 <li>
 Strong OT data engineering expertise including ingestion from historians, handling time-series characteristics, and ensuring data quality.
 </li>
 <li>
 Ability to design scalable, secure OT-to-IT data pipelines with governance, lineage, and auditability.
 </li>
 <li>
 Advanced pipeline engineering practices (reliability, observability, orchestration, performance tuning).
 </li>
 <li>
 Stakeholder leadership across plant operations, OT engineering, IT, and analytics consumers.
 </li>
 <li>
 Vendor assurance and technical governance for complex multi-site delivery programs.
 </li>
 </ul>
</div>

Principal Specialist, Engineering and ETL (OT)

MOZN

<div>
 
 
 About Mozn
 
 
 
 
 
 MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
 
 
 We're a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
 
 
 If you're passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
 
 
 
 About the role
 
 
 
 
 
 We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.
 
 
 What you'll do
 
 
 
 
 <ul>
 <li>
 Designing, building, and scaling machine learning models and infrastructure
 </li>
 <li>
 Deploying deep learning and generative models into production for public and private sector projects
 </li>
 <li>
 Optimizing ML training and inference for performance, latency, and scalability
 </li>
 <li>
 Monitoring, retraining, and improving deployed ML models
 </li>
 <li>
 Driving consultation efforts, providing expert guidance to client stakeholders
 </li>
 <li>
 Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations
 </li>
 <li>
 Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data
 </li>
 <li>
 Develop backend services and APIs to expose AI capabilities securely and reliably
 </li>
 <li>
 Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions
 </li>
 <li>
 Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 <ul>
 <li>
 Bachelor's or master's degree in computer science or related field
 </li>
 <li>
 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI
 </li>
 <li>
 Strong track record of projects across public and private sectors
 </li>
 <li>
 Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
 </li>
 <li>
 Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
 </li>
 <li>
 Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
 </li>
 <li>
 Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services
 </li>
 <li>
 Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
 </li>
 <li>
 Familiarity with MLOps practices and automation pipelines
 </li>
 <li>
 Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment
 </li>
 <li>
 Experience building data ingestion, transformation, and processing pipelines
 </li>
 <li>
 Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies
 </li>
 <li>
 Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces
 </li>
 <li>
 Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS
 </li>
 <li>
 Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services
 </li>
 <li>
 Ability to independently build functional AI applications from prototype through production
 </li>
 <li>
 Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery
 
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 
 <ul>
 <li>
 You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
 </li>
 </ul>
 <ul>
 <li>
 You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
 </li>
 </ul>
 <ul>
 <li>
 The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
 </li>
 </ul>
 <ul>
 <li>
 You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
 </li>
 </ul>
 <ul>
 <li>
 We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
 </li>
 </ul>
</div>

AI Engineer

Qualcomm

<div>
 
 
 Company:
 
 
 
 
 Qualcomm Middle East Information Technology Company LLC
 
 
 
 
 Job Area:
 
 
 
 
 Engineering Group, Engineering Group &gt; Software Engineering
 
 
 
 
 General Summary:
 
 
 
 
 
 About Us
 
 
 
 Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You&rsquo;ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.
 
 
 Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region.
 
 
 As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
 
 
 
 
 About The Role
 
 
 
 
 We are seeking a Full-Stack Machine Learning Engineer to join our team, bridging AI solutions development with AI platform engineering for Qualcomm&rsquo;s AI Inference Suite and rack-scale data center deployments. This role involves designing, delivering, and supporting end-to-end AI services, agentic workflows, and fine-tuning pipelines, while enabling lifecycle automation, orchestration, and observability for large-scale data center environments.
 
 
 You will bring a strong combination of full-stack engineering expertise, machine learning proficiency, and infrastructure knowledge to build robust, scalable AI systems.
 
 
 
 
 Key Responsibilities Will Include:
 
 
 
 
 <ul>
 <li>
 API Development &amp; Optimization: Build and optimize API serving layers for AI inference workloads, ensuring model and hardware efficiency.
 </li>
 <li>
 Agentic Workflows &amp; RAG Pipelines: Develop intelligent agents and retrieval-augmented generation workflows using frameworks such as LangChain and crew.ai.
 </li>
 <li>
 Model Lifecycle Management: Implement production-grade bring-your-own-model and fine-tuning flows, including dataset ingestion, orchestration, evaluation, and deployment.
 </li>
 <li>
 LLM Runtime Integration: Work with various LLM runtimes (e.g., vLLM, Dynamo, llm-d) and leverage inference optimization techniques.
 </li>
 <li>
 SDK &amp; Tooling Contributions: Contribute to AI Inference Suite SDKs (Python/TypeScript/Java/Rust), CLI tools, and reference applications.
 </li>
 <li>
 Cluster Management: Design and maintain AI cluster management software for provisioning, orchestration, and monitoring.
 </li>
 <li>
 Telemetry &amp; Observability: Integrate out-of-band management via Redfish/IPMI and in-band telemetry using Prometheus/OpenTelemetry.
 </li>
 <li>
 Infrastructure-as-Code: Develop workflows using MAAS, Terraform, and Ansible for bare-metal and containerized deployments.
 </li>
 <li>
 Kubernetes Orchestration: Enable Kubernetes/Helm-based orchestration for inference clusters and multi-tenancy.
 </li>
 <li>
 Monitoring &amp; Dashboards: Build dashboards for rack health, inventory, and SLA compliance.
 </li>
 <li>
 Continuous Innovation: Stay current with GenAI trends, rack-scale AI orchestration, and data center best practices.
 
 
 
 </li>
 </ul>
 
 
 Minimum Qualifications
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, or related field.
 </li>
 <li>
 5+ years of software engineering experience; 3+ years in ML or HPC environments.
 </li>
 <li>
 Strong programming skills in Python, Rust/Go, and TypeScript, with solid software development fundamentals.
 </li>
 <li>
 Deep understanding of data structures and algorithms in distributed systems and high-performance computing contexts.
 </li>
 <li>
 Hands-on experience with Kubernetes, Helm, Prometheus/OpenTelemetry, and Ansible/Terraform.
 </li>
 <li>
 Practical experience with LLM runtimes, agent frameworks, and rack-scale orchestration.
 
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Computer Science, Machine Learning, or related field.
 </li>
 <li>
 Experience building inference and fine-tuning pipelines, as well as agentic workflows.
 </li>
 <li>
 Knowledge of data centre resource lifecycle management, out-of-band protocols (Redfish/IPMI), and MAAS/OpenStack.
 </li>
 <li>
 Exposure to scale-up data centre networking technologies (RoCE/RDMA/NVLink).
 </li>
 <li>
 Contributions to inference and GenAI model performance optimization.
 
 
 
 </li>
 </ul>
 
 
 What's On Offer
 
 
 
 
 Apart from working with great people, we offer the below:
 
 
 <ul>
 <li>
 Salary including housing &amp; transport allowance
 </li>
 <li>
 Stock (RSU's) and performance related bonus
 </li>
 <li>
 16 weeks fully paid Maternity Leave
 </li>
 <li>
 6 weeks fully paid Paternity Leave
 </li>
 <li>
 Employee stock purchase scheme
 </li>
 <li>
 Child Education Allowance
 </li>
 <li>
 Relocation and immigration support (if needed)
 </li>
 <li>
 Life and Medical Insurance
 </li>
 <li>
 Live+ Well Reimbursement for health and recreational membership fees
 
 
 
 </li>
 </ul>
 
 
 Minimum Qualifications:
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
 
 </li>
 </ul>
 OR
 
 
 Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
 
 
 OR
 
 
 PhD in Engineering, Information Systems, Computer Science, or related field.
 
 
 <ul>
 <li>
 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
 </li>
 <li>
 References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
 
 
 
 </li>
 </ul>
 Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
 
 
 Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
 
 
 
 To all Staffing and Recruiting Agencies
 
 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
 
 
 If you would like more information about this role, please contact Qualcomm Careers.
</div>

Full Stack Machine Learning Engineer (Datacentre AI Engineering) - Riyadh, KSA

Wisayah Investment Company

<div>
 
 
 Role Description
 
 
 
 
 
 
 
 
 
 The Data Scientist Senior Analyst plays a key role in embedding advanced analytics and AI-enabled capabilities into day-to-day investment and operational workflows. The role combines business-facing enablement with hands-on solution development&mdash;working across teams to improve how data is used, decisions are made, and processes are executed.
 
 
 
 
 
 The position begins with a strong focus on understanding the firm&rsquo;s data ecosystem and internal workflows and evolves into designing and building scalable solutions&mdash;from workflow automation to more advanced, model-driven applications that support the firm&rsquo;s broader digital transformation.
 
 
 
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 
 
 
 1. Enablement &amp; Use-Case Development
 
 
 <ul>
 <li>
 Partner with teams across front, middle, and back office to identify where automation and AI can improve real workflows.
 </li>
 <li>
 Guide business teams in designing and adopting their own enhanced workflows, providing hands-on support, frameworks, and review.
 </li>
 <li>
 Structure business problems into clearly defined use cases, including requirements, prioritization, and expected impact.
 </li>
 <li>
 Maintain and track a centralized pipeline of initiatives, including progress, adoption, and outcomes (e.g., efficiency gains, quality improvements).
 </li>
 </ul>
 
 
 
 
 
 2. Solution Development &amp; Automation
 
 
 <ul>
 <li>
 Design and build practical solutions that enhance workflows, including automation, data-driven tools, and intelligent assistants.
 </li>
 <li>
 Develop and deploy AI-supported applications (e.g., agents, document/query solutions) with appropriate controls and reliability considerations.
 </li>
 <li>
 Support implementation of retrieval and knowledge-access solutions that make internal data and content more usable.
 </li>
 <li>
 Integrate solutions with internal systems and support end-to-end automation of recurring processes.
 </li>
 </ul>
 
 
 
 
 
 3. Data Landscape &amp; Foundations
 
 
 <ul>
 <li>
 Build a deep understanding of the firm&rsquo;s data architecture, including internal systems, vendor platforms, and document repositories.
 </li>
 <li>
 Map key data sources and flows to ensure solutions are grounded in what the data can support.
 </li>
 <li>
 Identify and help address gaps in data accessibility, quality, and structure that impact analytics and automation use cases.
 </li>
 </ul>
 
 
 
 
 
 4. Stakeholder &amp; Delivery Management
 
 
 <ul>
 <li>
 Act as a bridge between business stakeholders and technical or external partners.
 </li>
 <li>
 Support delivery and implementation efforts through hands-on involvement, review, and coordination.
 </li>
 <li>
 Contribute to evaluation and onboarding of new tools and platforms, including initial assessment of data handling considerations.
 </li>
 </ul>
 
 
 
 
 
 5. Continuous Development &amp; Innovation
 
 
 <ul>
 <li>
 Stay up to date with developments in investment management, data, and applied AI.
 </li>
 <li>
 Contribute to evolving the firm&rsquo;s capabilities by progressively taking on more advanced technical and solution-building responsibilities.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Skills
 
 
 
 
 
 <ul>
 <li>
 Investment Management
 </li>
 <li>
 Business &amp; Use-Case Structuring
 </li>
 <li>
 Data Analysis &amp; Automation
 </li>
 <li>
 Workflow Optimization
 </li>
 <li>
 Stakeholder Management
 </li>
 <li>
 Communication
 </li>
 <li>
 Applied AI / Emerging Technologies
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Requirements
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in finance, Economics, Business, Computer Science, Management Information System or a related field.
 </li>
 <li>
 4&ndash;7 years of experience combining investment domain knowledge with hands-on analytics, automation, or AI-related work.
 </li>
 <li>
 Proven ability to deliver practical solutions (e.g., automation, reporting tools, intelligent workflows) that are adopted by end users.
 </li>
 <li>
 Strong ability to translate between business needs and technical requirements.
 </li>
 <li>
 Familiarity with tools such as SQL, Python, or similar; experience working with data-driven workflows is preferred.
 </li>
 <li>
 Strong communication skills and experience working across cross-functional teams.
 </li>
 <li>
 High ownership mindset, with comfort operating in evolving and ambiguous environments.
 </li>
 </ul>
</div>

Data Scientist

Explore 240+ Data engineer in Saudi Arabia this August. Find roles across top companies and apply now to boost your career.

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