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intelmatix

<div>
 
 About Intelmatix
 
 
 
 Intelmatix is a deep tech Artificial intelligence (AI) company founded in July 2021 by a group of MIT scientists with the vision of transforming enterprises to become cognitive. A cognitive enterprise is one that uses AI and Decision Intelligence in making their decisions. This leads to better business decisions with improved accuracy, reduced errors, and better outcomes across various aspects of the business.
 
 
 
 About The Role
 
 
 
 We are seeking a highly experienced Senior Data Engineer to lead the technical design, implementation, and delivery of an enterprise-grade, AI-ready Data Lakehouse. This role is critical to establishing the foundational data layer for a massive digital transformation initiative, designed to power advanced Artificial Intelligence (AI) agents, digital workers, and complex knowledge graphs (Ontologies).
 
 
 The ideal candidate will have a strong background in software development with a focus on building and optimizing data pipelines, ensuring data quality, and integrating data from various sources. As a Senior Data Engineer, you will play a key role in designing, developing, and maintaining scalable data infrastructure that supports our business intelligence and analytics efforts.
 
 
 Based in Riyadh, you will be responsible for architecting a highly secure platform that complies with strict national data residency and cybersecurity standards. You will not only build the system but also act as a technical leader, mentoring client engineering teams through a collaborative "co-build" model to ensure long-term operational ownership.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Lakehouse Architecture &amp; Implementation: Design and deploy a unified Data Lakehouse utilizing the Medallion architecture (Bronze, Silver, Gold) and open table formats (e.g., Delta Lake, Apache Iceberg) on cloud infrastructure hosted within Saudi Arabia.
 </li>
 <li>
 Data Ingestion &amp; Pipeline Engineering: Build reusable, automated ingestion frameworks (batch and streaming) capable of processing both structured data (RDBMS, APIs) and unstructured data (PDFs, policy documents) to feed downstream AI models and semantic reasoning engines.
 </li>
 <li>
 Data Quality &amp; Governance: Implement automated data quality "circuit breakers" (completeness, uniqueness, referential integrity) and end-to-end data lineage tracking frameworks.
 </li>
 <li>
 Optimization: Optimize data processing workflows for performance, scalability, and cost-efficiency.
 </li>
 <li>
 System Monitoring and Maintenance: Monitor and maintain data systems, responding to SEVs or other urgent issues to ensure continuous operations.
 </li>
 <li>
 Security &amp; Compliance: Ensure the platform adheres strictly to NCA (National Cybersecurity Authority) and NDMO (National Data Management Office) standards. Implement AES-256 encryption at rest, TLS 1.2+ in transit, robust Key Management Systems (KMS), and centralized audit logging.
 </li>
 <li>
 Access Control Integration: Design and deploy granular Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC), integrating seamlessly with existing enterprise Identity Providers (e.g., Active Directory).
 </li>
 <li>
 Capability Building &amp; Handover: Lead hands-on knowledge transfer sessions, pair-programming with client engineers, creating operational runbooks, and conducting "Game Day" failure simulations to ensure the client&rsquo;s team is fully ready to operate the platform independently.
 
 
 </li>
 </ul>
 
 Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Education: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field.
 </li>
 <li>
 Experience: 5+ years of proven experience in Data Engineering, Distributed Systems, or Big Data Architecture, with at least 2+ years specifically leading Data Lakehouse or Cloud Data Platform implementations.
 </li>
 <li>
 Technical Skills &amp; Core Technologies:
 </li>
 <ul>
 <li>
 Programming Languages: Proficiency in programming languages such as Python, Java, or Scala.
 </li>
 <li>
 Data Architecture &amp; System Design: Strong expertise in designing data-intensive applications, complex data modeling, and schema design for enterprise environments.
 </li>
 <li>
 Distributed Systems &amp; Lakehouse Technologies: Deep, hands-on experience with distributed processing engines (e.g., Apache Spark, Kafka, Hadoop) and modern open table formats (e.g., Delta Lake, Apache Iceberg, Apache Hudi).
 </li>
 <li>
 ETL/ELT &amp; Orchestration: Experience designing and building robust data pipelines using modern transformation and orchestration tools (e.g., Apache Airflow, Prefect, dbt).
 </li>
 <li>
 Database Ecosystems: Proven track record with relational databases (e.g., PostgreSQL, MySQL), NoSQL platforms (e.g., MongoDB, Cassandra), and distributed SQL query engines like Hive and Trino.
 </li>
 <li>
 Cloud Infrastructure: Proven experience deploying enterprise data solutions on major cloud providers, specifically within localized Saudi cloud regions. Expertise in Oracle Cloud Infrastructure (OCI) or Google Cloud Platform (GCP) is highly preferred, though experience with AWS or Azure is acceptable.
 </li>
 </ul>
 <li>
 Analytical Skills: Strong problem-solving skills with a keen eye for detail and a passion for data.
 </li>
 <li>
 AI/Data Science Enablement: Prior experience building data pipelines optimized for Machine Learning, Natural Language Processing (NLP), vector embeddings, or Knowledge Graphs/Ontologies is highly desirable.
 </li>
 <li>
 Security &amp; Networking: Strong understanding of enterprise network security, Private Endpoints, Identity &amp; Access Management (IAM), and cryptographic key management.
 </li>
 <li>
 Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
 </li>
 <li>
 Leadership Skills: Demonstrated ability to lead technical teams, manage stakeholder expectations, and successfully transition complex systems to internal IT/Data teams.
 </li>
 <li>
 Regulatory Knowledge: Familiarity with Saudi Arabian data compliance frameworks (NCA CCC, NDMO, SDAIA) is highly preferred.
 </li>
 </ul>
</div>

Senior Data Engineer

TAWANTECH

<div>Job Summary
We are seeking a highly skilled and motivated Senior Data Engineer to design, develop, and optimize scalable data platforms and pipelines within the banking and financial services domain. The ideal candidate will have strong expertise in Python, SQL, big data technologies, and cloud-based data ecosystems. You will be responsible for building robust, secure, and scalable data solutions that support regulatory reporting, risk management, customer analytics, and business intelligence initiatives.
Key Responsibilities<ul><li>
Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of banking and financial data.</li><li>
Build and optimize data workflows using Apache Spark and Apache Airflow.</li><li>
Design and implement Data Warehouse and Data Lake architectures to support enterprise banking analytics and reporting requirements.</li><li>
Develop and maintain high-performance data models for transactional, customer, risk, and regulatory data.</li><li>
Collaborate with business stakeholders, data analysts, risk teams, and compliance teams to deliver data-driven solutions.</li><li>
Ensure data quality, governance, security, and regulatory compliance across data platforms.</li><li>
Implement monitoring, troubleshooting, and performance tuning for data pipelines and processing frameworks.</li><li>
Leverage cloud platforms or Cloudera ecosystem technologies to build and manage modern data infrastructure.</li><li>
Drive CI/CD implementation and DataOps best practices to improve deployment efficiency and operational reliability.</li><li>
Support regulatory reporting, audit requirements, and data lineage initiatives.</li><li>
Mentor junior engineers and contribute to technical architecture and best practices.</li></ul> 

Requirements 
 
Required Qualifications<ul><li>
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.</li><li>
4+ years of hands-on experience in Data Engineering.</li><li>
Strong programming skills in Python and advanced SQL.</li><li>
Experience with Apache Spark for large-scale data processing.</li><li>
Experience with Apache Airflow for workflow orchestration and scheduling.</li><li>
Solid understanding of Data Warehouse and Data Lake architectures.</li><li>
Proven experience building and maintaining ETL/ELT pipelines.</li><li>
Experience working with cloud platforms (AWS, Azure, or GCP) or the Cloudera ecosystem.</li><li>
Strong knowledge of data modeling techniques and performance optimization strategies.</li><li>
Experience implementing CI/CD pipelines and DataOps methodologies.</li><li>
Banking or Financial Services domain experience with exposure to financial data, regulatory reporting, risk, compliance, or customer analytics.</li><li>
Excellent problem-solving, analytical, and communication skills.</li></ul>
Preferred Qualifications<ul><li>
Experience with banking data domains such as Core Banking, Payments, Lending, Treasury, Risk, AML, KYC, or Regulatory Reporting.</li><li>
Knowledge of financial data governance, security, and compliance standards.</li><li>
Experience with real-time and batch data processing in highly regulated environments.</li><li>
Familiarity with containerization technologies such as Docker and Kubernetes.</li><li>
Experience with data lineage, metadata management, and data quality frameworks.</li></ul></div>

Talent 360

<div>About Us 
We are building the next-generation Office of the CFO that simplifies finance for all businesses. 
SiFi is a corporate expense management platform designed to empower accounting teams with seamless control over corporate spending. Our platform allows companies to issue cards with specific spending restrictions, ensuring funds are used efficiently and only for approved expenses. 
As we scale, trusted data becomes core infrastructure powering financial correctness, operational visibility, and AI-powered automation. 
About the Role 
We are looking for a Senior Data Engineer to help define and scale the foundation of SiFi&rsquo;s data platform. 
You will be part of the Data &amp; AI team and serve as a key partner to Finance, Product, Engineering, Operations, and Compliance. Your primary responsibility will be to design and own our data platform, modeling standards, and AI-ready infrastructure, ensuring that metrics are accurate, scalable, and trusted across the organization. 
This is a high-ownership role focused on building financial data infrastructure from first principles. 
This role is based in Saudi Arabia (Relocation). 
What You Will Own 
Data Modeling and Standards 
<ul><li>
Define and maintain scalable data models in SQL 
</li><li>
Establish structured warehouse layers and modeling best practices 
</li><li>
Own KPI definitions and ensure a single source of truth 
</li><li>
Ensure financial correctness and metric consistency</li></ul> 
Warehouse Architecture 
<ul><li>
Design and evolve our cloud data warehouse in BigQuery 
</li><li>
Own transformation workflows using dbt, SQLMesh, or similar tools 
</li><li>
Optimize performance, reliability, and cost 
</li><li>
Design and support production-grade AI/ML pipelines ensuring model performance, data integrity, and compliance.</li></ul> 
Reliability and Governance 
<ul><li>
Ensure data quality, integrity, and observability 
</li><li>
Implement access controls aligned with compliance requirements 
</li><li>
Build a scalable foundation ready for advanced analytics and AI</li></ul> 
Cross-Functional Impact 
<ul><li>
Translate business requirements into robust data systems 
</li><li>
Enable trusted reporting and BI across teams 
</li><li>
Support experimentation and AI-driven initiatives with well-structured datasets</li></ul> 

Requirements 
What We Are Looking For 
<ul><li>
5+ years of experience in Data Engineering or Analytics Engineering 
</li><li>
Strong SQL expertise with hands-on data modeling experience 
</li><li>
Experience with cloud data warehouses such as BigQuery 
</li><li>
Experience with modern transformation frameworks such as dbt or SQLMesh 
</li><li>
Experience building or supporting production-grade AI/ML pipelines is a strong plus 
</li><li>
Ability to operate independently in a fast-moving startup 
</li><li>
Operates with high agency, taking end-to-end ownership of complex problems and delivering outcomes</li></ul></div>

Senior AI Data Engineer

aramco digital

<div>
 
 
 Overview:
 
 
 
 The Sr. AI &amp; Data Expert is a highly skilled individual contributor responsible for designing and implementing advanced AI systems and scalable data platforms. This role focuses on building next generation AI solutions&mdash;including agentic AI systems, LLM-based applications, and industrial data pipelines&mdash;that transform data into actionable business outcomes. The position requires deep expertise across AI/ML, data engineering, and cloud platforms, along with the ability to translate business needs into technically robust and production-ready solutions.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design and implement agentic AI systems, including multi-agent frameworks and autonomous workflows
 </li>
 <li>
 Develop and optimize RAG pipelines, LLM integrations, and model fine-tuning for real-world applications
 </li>
 <li>
 Build production-grade AI services and APIs, ensuring scalability, performance, and reliability
 </li>
 <li>
 Design and implement scalable data architectures for structured and unstructured data
 </li>
 <li>
 Build and maintain data pipelines supporting ingestion, processing, and consumption layers
 </li>
 <li>
 Ensure data quality, consistency, and availability across AI and analytics workloads
 </li>
 <li>
 Troubleshoot and resolve complex technical challenges across AI, data, and platform layers
 </li>
 <li>
 Optimize systems for performance, latency, and cost efficiency, especially in high-scale environments
 </li>
 <li>
 Contribute to reusable components, frameworks, and engineering best practices
 </li>
 <li>
 Implement and maintain end-to-end ML/LLM lifecycle workflows, including training, deployment, and monitoring
 </li>
 <li>
 Integrate CI/CD pipelines for AI systems and automate model validation, testing, and releases
 </li>
 <li>
 Monitor model performance, drift, and system health in production
 </li>
 <li>
 Design and deploy AI/data solutions across multi-cloud or hybrid environments, including GPU-based workloads
 </li>
 <li>
 Work with modern infrastructure stacks to support scalable AI processing and storage
 </li>
 <li>
 Ensure efficient utilization of compute resources and cloud services
 </li>
 <li>
 Apply data governance, security, and compliance standards, including data sovereignty requirements
 </li>
 <li>
 Implement Responsible AI practices, ensuring transparency, fairness, and secure model usage
 </li>
 <li>
 Contribute to defining guardrails for safe and compliant AI deployment
 </li>
 <li>
 Translate business requirements into AI and data solutions aligned with KPIs and measurable outcomes
 </li>
 <li>
 Collaborate with product, engineering, and business teams to deliver end-to-end solutions
 </li>
 <li>
 Provide technical input to support decision-making and solution design
 </li>
 <li>
 Contribute to documentation, standards, and reusable assets.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 
 
 Education:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Master&rsquo;s degree is a plus.
 </li>
 </ul>
 
 
 
 
 
 Experience:
 
 
 <ul>
 <li>
 10&ndash;14 years of experience in AI/ML, data engineering, or related domains
 </li>
 <li>
 Strong hands-on experience building and deploying AI/ML systems in production
 </li>
 <li>
 Experience with LLMs, RAG pipelines, and modern AI frameworks
 </li>
 <li>
 Exposure to large-scale data platforms and distributed systems
 </li>
 <li>
 Experience working in cloud environments (multi-cloud preferred)
 </li>
 </ul>
 
 
 
 
 
 Skills &amp; Competencies:
 
 
 <ul>
 <li>
 AI/ML development (LLMs, RAG, model fine-tuning)
 </li>
 <li>
 Data engineering and pipeline development
 </li>
 <li>
 MLOps / LLMOps practices and tooling
 </li>
 <li>
 Backend development (Python and related frameworks)
 </li>
 <li>
 Distributed systems and scalable architectures
 </li>
 <li>
 AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain or similar)
 </li>
 <li>
 Data processing tools (e.g., Spark, Airflow, Prefect)
 </li>
 <li>
 Containerization and orchestration (Docker, Kubernetes)
 </li>
 <li>
 Cloud platforms (AWS, Azure, GCP)
 </li>
 <li>
 Observability and monitoring tools
 </li>
 </ul>
</div>

Sr. AI & Data Expert

Emdad By Elm

<div>
 
 
 Job Description:
 
 
 
 The
 
 Commvault Senior Engineer
 
 is responsible for the implementation, administration, optimization, and support of the
 
 Commvault
 
 data protection environment. The role requires deep technical expertise in backup, recovery, storage, and disaster recovery solutions. The engineer will act as the primary technical contact for all Commvault-related operations, ensuring system stability, performance, and compliance with best practices.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 1. Administration &amp; Support
 
 
 <ul>
 <li>
 
 Backup and Recovery
 
 : Design, implement, and manage backup and recovery processes for critical data
 </li>
 <li>
 Manage and maintain the Commvault backup infrastructure.
 </li>
 <li>
 Configure, monitor, and troubleshoot backup and restore jobs.
 </li>
 <li>
 Perform regular Commvault backup infra health checks and system performance tuning.
 </li>
 <li>
 Ensure successful backups and proactive issue resolution.
 </li>
 <li>
 Storage Capacity
 
 Planning: Monitor storage usage and plan
 
 for future capacity needs.
 </li>
 <li>
 Performance Optimization:
 
 Optimize backup and storage performance
 
 to minimize downtime.
 </li>
 <li>
 Manage storage policies, retention rules, and media management.
 </li>
 <li>
 Setup offline backup polices and maintain
 </li>
 <li>
 Creating and managing
 
 HyperMetro and HyperReplication
 
 for disaster recovery
 </li>
 <li>
 Administration of Tape Library like hardware issues, software upgrade, and Tape cartridges
 </li>
 </ul>
 
 
 
 
 
 2. Implementation &amp; Upgrades
 
 
 <ul>
 <li>
 Install, configure, and upgrade Commvault components with hardware and software part
 </li>
 <li>
 
 Implement new backup requirements for servers, databases, virtual machines.
 
 </li>
 <li>
 Perform patching and version upgrades following best practices.
 </li>
 </ul>
 
 
 
 
 
 3. Disaster Recovery &amp; Backup Testing
 
 
 <ul>
 <li>
 
 Develop and maintain disaster recovery procedures.
 
 </li>
 </ul>
 
 
 
 
 
 
 <ul>
 <li>
 Conduct periodic restore testing and DR drills.
 </li>
 <li>
 Verify backup integrity and data recoverability
 </li>
 <li>
 Ensure
 
 RPO/RTO objectives are met.
 
 </li>
 </ul>
 
 
 
 
 
 4. Monitoring &amp; Reporting
 
 
 <ul>
 <li>
 Create regular backup reports and capacity planning reports.
 </li>
 <li>
 Proactively identify risks and recommend improvements.
 </li>
 <li>
 Maintain documentation of configurations and procedures.
 </li>
 </ul>
 
 
 
 
 
 5. Integration &amp; Infra Support
 
 
 
 
 
 <ul>
 <li>
 Integrate Commvault with:
 
 VMware (vCenter/ESXi)
 
 </li>
 <li>
 
 Physical and virtual servers (Windows/Linux)
 
 </li>
 <li>
 
 Databases (DB2,SQL, POSTGRESS, Oracle etc)
 
 </li>
 <li>
 
 Storage (FC, VSAN etc.)
 
 </li>
 <li>
 Coordinate with storage, virtualization, and network teams.
 </li>
 </ul>
 
 
 
 
 
 6. Incident &amp; Change Management
 
 
 <ul>
 <li>
 Handle incident resolution within SLA.
 </li>
 <li>
 Participate in change management processes.
 </li>
 <li>
 Work with vendor support for advanced troubleshooting.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 
 Bachelor&rsquo;s
 
 degree in Computer Science, IT, or related field.
 </li>
 <li>
 
 6&ndash;8 years of experience in enterprise backup solutions.
 
 </li>
 <li>
 Strong hands-on experience with Commvault administration.
 </li>
 <li>
 
 Experience with:
 
 </li>
 </ul>
 
 - VMware and Nutanix Infra
 
 
 - SAN/NAS storage
 
 
 - Windows &amp; Linux servers and virtual appliances
 
 
 - Database backup strategies
 
 <ul>
 <li>
 Knowledge of DR planning and implementation.
 </li>
 <li>
 Strong troubleshooting and analytical skills.
 </li>
 </ul>
 
 
 
 
 
 Preferred Certifications
 
 
 <ul>
 <li>
 
 Commvault Certified Engineer (CCE)
 
 </li>
 <li>
 
 Linux
 
 </li>
 </ul>
 
 
 
 
 
 Key Skills
 
 
 <ul>
 <li>
 Backup &amp; Recovery Architecture
 </li>
 <li>
 Disaster Recovery Planning
 </li>
 <li>
 Performance Tuning
 </li>
 <li>
 Storage Management
 </li>
 <li>
 Documentation &amp; Reporting
 </li>
 </ul>
 
 
 
 
 
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and coordination skills
 </li>
 <li>
 Proactive problem-solving approach
 </li>
 <li>
 Ability to work under pressure and meet SLAs
 </li>
 </ul>
</div>

Commvault Senior Engineer

MASTER-WORKS

<div>Business Unit: Nabeh
Job Location: HQ
Job Purpose
Our subsidiary Nabeh is seeking for an experienced and highly skilled Software Testing, Senior Engineer. Responsible for designing, executing, and optimizing testing activities across AI and digital systems, ensuring high-quality delivery and supporting automation and performance initiatives.
Key Responsibilities<ul><li>
Design and maintain:
</li><li><ul><li>Test cases, test scenarios, and test data
</li></ul></li><li>Execute:
</li><li><ul><li>Functional, system, and integration testing
</li><li>API testing (Swagger, Postman)
</li></ul></li></ul><ul><li>Develop and maintain automation scripts (Selenium, Robot, SHAFT)
</li><li>Support performance testing execution (JMeter, Locust, Gatling, k6)
</li><li>Perform database validation and data consistency checks
</li><li>Validate AI outputs against defined scenarios and expected behavior
</li><li>Log, track, and manage defects with proper documentation
</li><li>Prepare test reports and execution evidence
</li><li>Collaborate with development, data, and AI teams
</li><li>Mentor and guide junior engineers
</li></ul>Qualifications &amp; Requirements<ul><li>
4&ndash;6+ years of QA experience
</li><li>Arabic Speaker (Mandatory)</li><li>
Strong hands-on experience in:
</li><li><ul><li>Test case design &amp; execution
</li><li>API and database testing
</li></ul></li></ul><ul><li>Working knowledge of automation frameworks
</li><li>Good understanding of performance testing concepts
</li><li>Exposure to AI systems or data-driven platforms (preferred)
</li><li>Experience in Agile environments
</li></ul>Certifications<ul><li>
ISTQB CTFL (Mandatory)
</li><li>ISTQB CTFL-AT (Preferred)
</li></ul>Language<ul><li>
Arabic (Native) &amp; English (Fluent)</li></ul></div>

Software Testing, Senior Engineer

DeepSource Technologies

<div>We are looking for a highly capable Senior AI Engineer / MLOps Engineer to join our team and lead the design, development, deployment, and optimization of scalable, production-grade AI and machine learning solutions. The ideal candidate will have strong hands-on experience across AI engineering, machine learning, MLOps, cloud-native architecture, and data engineering, with the ability to transform experimentation into reliable, business-ready systems.
This role requires deep expertise in LLMs, RAG, agentic AI workflows, CI/CD automation, production ML lifecycle management, and modern data platforms. The selected candidate will be expected to lead end-to-end AI initiatives, work across multiple projects, collaborate with technical and business stakeholders, and ensure operational excellence across AI platforms.
Key Responsibilities<ul><li>Design, develop, deploy, and maintain production-grade AI and machine learning systems end to end.</li><li>Build and optimize LLM-powered applications, including RAG pipelines, prompt workflows, agent-based systems, and multimodal AI use cases.</li><li>Develop intelligent workflows using tool-calling, orchestration frameworks, and contextual reasoning patterns.</li><li>Fine-tune, evaluate, and operationalize machine learning and foundation models for enterprise use cases.</li><li>Build and manage MLOps pipelines covering training, evaluation, model registration, deployment, monitoring, and retraining.</li><li>Implement CI/CD pipelines for ML and AI workflows to support automated testing, release management, and controlled deployments.</li><li>Establish model monitoring frameworks for drift detection, feature attribution, inference quality, and performance tracking.</li><li>Ensure reproducibility, reliability, and version control across AI/ML environments.</li><li>Architect scalable AI/ML platforms using modern compute, storage, orchestration, monitoring, and search services.</li><li>Build repeatable environments using Infrastructure as Code.</li><li>Support secure, high-availability, and cost-efficient deployment models across development, staging, and production environments.</li><li>Design scalable inference and serving patterns for variable workloads.</li><li>Build and maintain automated data pipelines, ETL/ELT workflows, and data processing frameworks for AI/ML consumption.</li><li>Ensure data quality, lineage, governance, and versioning to support dependable model training and inference.</li><li>Work with structured and unstructured datasets across data lakes, data warehouses, and operational systems.</li><li>Deliver analytics-ready datasets to downstream systems and applications.</li><li>Lead multiple AI initiatives in parallel, including planning, execution, and coordination with internal teams and stakeholders.</li><li>Work closely with product, engineering, data, and business teams to deliver production-ready AI capabilities.</li><li>Contribute to architecture decisions, technical documentation, best practices, and engineering standards.</li><li>Support knowledge sharing, technical leadership, and continuous improvement across the AI function. 
</li></ul> 
 
Requirements<ul><li> 
Bachelor&rsquo;s degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>5+ years of hands-on experience in AI engineering, machine learning engineering, MLOps, or data/ML platform engineering.</li><li>Proven experience deploying production AI/ML solutions in enterprise environments.</li><li>Strong programming experience in Python and SQL.</li><li>Strong experience with enterprise AI/ML architecture and delivery.</li></ul></div>

AI Architect - Riyadh,KSA

Explore 472+ Senior data engineer in Saudi Arabia this June. Find roles across top companies and apply now to boost your career.

472 senior data engineer jobs In Saudi Arabia

Senior Data Engineer

Senior Data Engineer

Senior AI Data Engineer

Sr. AI & Data Expert

Commvault Senior Engineer

Software Testing, Senior Engineer

AI Architect - Riyadh,KSA