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ai ml support automation analyst

King Abdullah University of Science and Technology

<div></div><div><p><b>Date: </b>May 19, 2026
</p><p><b>Location:</b> Saudi Arabia
</p><p><b>Company: </b>King Abdullah University of Science &amp; Technology
</p><div><p>Position Summary</p>
<p>
The AI/ML Support Automation Analyst will be a key member of the KSL AI Support Team, focusing on MLOps</p>
<p>
infrastructure, container orchestration, and workflow automation at a supercomputing scale. Working under the</p>
<p>
AI/ML Support Team Lead, this role is responsible for developing and maintaining secure, OCI-compliant container</p>
<p>
images, robust CI/CD pipelines, and cloud-native MLOps workflows that enable researchers to efficiently deploy and</p>
<p>
manage AI/ML workloads. The Analyst will bridge the gap between cutting-edge Kubernetes-based infrastructure</p>
<p>
and the diverse needs of the research community, contributing to governance, technical enablement, and</p>
<p>
community development initiatives.</p><br>
<p></p>
<p>
Major Responsibilities</p>
<p>
1<b> </b>MLOps and Container Development</p>
<ul><li>Providing timely and useful user support via telephone, walk-in, email, and ticketing system submissions</li></ul>
<p>
for all types of inquiries.</p>
<ul><li>Maintain high customer service standards in dealing with and responding to user issues and questions.</li></ul>
<ul><li>Develop and maintain secure, OCI-compliant, and HPC-ready AI/ML and data science software container</li></ul>
<p>
images</p>
<ul><li>Design and implement robust MLOps workflows and pipelines at supercomputing scale</li></ul>
<ul><li>Develop and maintain CI/CD pipelines for reproducible infrastructure and workflow deployment</li></ul>
<ul><li>Design and deploy APIs for AI/ML services and inference endpoints</li></ul>
<ul><li>Implement and manage Kubernetes-based orchestration, including CNI, CSI, and service mesh</li></ul>
<p>
configurations and optimization</p>
<ul><li>Deploy and maintain container registries (Harbor) and model registries (MLFlow, Kubeflow Model</li></ul>
<p>
Registry)</p>
<p>
2<b> </b>Governance and Compliance Support</p>
<ul><li>Assist in computational readiness reviews for AI research projects</li></ul>
<ul><li>Assist in AI model and artifact control reviews to ensure compliance with institutional standards</li></ul>
<ul><li>Provide consultation to users on efficient resource usage for AI/ML and MLOps workflows</li></ul>
<ul><li>Ensure container images and workflows comply with security policies and best practices</li></ul>
<ul><li>Support the implementation of usage monitoring and reporting systems</li></ul>
<p>
3<b> </b>Performance and Benchmarking</p>
<ul><li>Perform performance debugging and tuning of MLOps and cloud-native workflows</li></ul>
<ul><li>Develop and maintain AI/ML and MLOps workload benchmarks for procuring new systems</li></ul>
<ul><li>Create and maintain regression testing workloads for existing clusters</li></ul>
<ul><li>Deploy and maintain observability and resource monitoring stacks using Prometheus, Grafana, NVIDIA</li></ul>
<p>
DCGM, and Grafana Loki</p>
<ul><li>Contribute to technology evaluation and benchmarking exercises for future infrastructure investments</li></ul>
<p>
4<b> </b>Training and Documentation</p>
<ul><li>Create comprehensive training content for users on MLOps platforms, Kubernetes, and containerization</li></ul>
<ul><li>Develop and maintain high-quality user documentation for automation tools and workflows</li></ul>
<ul><li>Support the delivery of workshops on CI/CD, container orchestration, and MLOps best practices</li></ul>
<ul><li>Contribute to knowledge transfer initiatives within the KAUST research community</li></ul>
<ul><li>Provide one-on-one consultation to researchers on efficient use of automation infrastructure</li></ul><br>
<p></p>
<p>
Personal Requirements</p>
<p>
Competencies</p>
<ul><li>Experience</li></ul>
<ul><li>Demonstrated experience developing robust and complex MLOps pipelines</li></ul>
<ul><li>Hands-on experience with API design and deployment</li></ul>
<ul><li>Experience developing robust and portable CI/CD pipelines for reproducible infrastructure and workflow</li></ul>
<p>
deployment</p>
<ul><li>Experience supporting researchers or working in academic/research computing settings preferred</li></ul>
<ul><li>Technical Skills - Essential</li></ul>
<ul><li>Kubernetes: Strong expertise in Kubernetes, Container Network Interface (CNI), Container Storage</li></ul>
<p>
Interface (CSI), and Service Mesh</p>
<ul><li>MLOps: Experience developing and maintaining MLOps pipelines and workflows</li></ul>
<ul><li>CI/CD: Proficiency in building CI/CD pipelines for infrastructure and application deployment</li></ul>
<ul><li>Containerization: Experience building secure, OCI-compliant container images</li></ul>
<ul><li>API Development: Experience in API design, development, and deployment</li></ul>
<ul><li>Programming: Proficiency in Python; experience with Go, Bash scripting</li></ul>
<ul><li>Linux: Strong Linux/Unix systems administration skills</li></ul>
<ul><li>Technical Skills - Desired</li></ul>
<ul><li>Experience with ArgoCD, Airflow, DASK, Spark for workflow orchestration</li></ul>
<ul><li>Experience with Kubeflow, KServe, and Seldon for ML serving and pipelines</li></ul>
<ul><li>Experience deploying and maintaining observability stacks (Prometheus, Grafana, NVIDIA DCGM, Grafana</li></ul>
<p>
Loki)</p>
<ul><li>Knowledge of Model Context Protocol (MCP) and agentic frameworks</li></ul>
<ul><li>Experience deploying inference services at scale</li></ul>
<ul><li>Experience deploying and maintaining container registries (Harbor) and model registries (MLFlow,</li></ul>
<p>
Kubeflow Model Registry, Artifact Hub)</p>
<ul><li>Experience with GitOps practices and Infrastructure as Code (Terraform, Ansible)</li></ul>
<ul><li>Experience with HPC schedulers (SLURM) and HPC-cloud integration</li></ul>
<ul><li>Soft Skills</li></ul>
<ul><li>Strong problem-solving and analytical abilities</li></ul>
<ul><li>Excellent written and verbal communication skills in English</li></ul>
<ul><li>Customer service mindset with patience for supporting diverse skill levels</li></ul>
<ul><li>Ability to work independently and as part of a collaborative team</li></ul>
<ul><li>Strong documentation and knowledge-sharing practices</li></ul>
<ul><li>Cultural sensitivity for working in an international environment</li></ul><br>
<p></p>
<p>
Preferred Qualifications</p>
<ul><li>Experience in national laboratories or major research computing facilities</li></ul>
<ul><li>Experience with GPU scheduling and resource management in Kubernetes</li></ul>
<ul><li>Background in DevOps or Site Reliability Engineering (SRE)</li></ul>
<ul><li>Contributions to open-source cloud-native or MLOps projects</li></ul>
<ul><li>Publications or presentations on MLOps, Kubernetes, or automation topics</li></ul>
<ul><li>Knowledge of Saudi Arabia's Vision 2030 and national AI initiatives</li></ul>
<ul><li>Additional certifications: AWS/Azure/GCP, Terraform, NVIDIA DLI</li></ul><br>
<p></p>
<p>
Qualifications</p>
<ul><li>Bachelor's or master&rsquo;s degree in computer science, Data Science, Computational Science, Artificial</li></ul>
<p>
Intelligence, or a related field</p>
<ul><li>Certifications such as CKA (Certified Kubernetes Administrator), CKAD (Certified Kubernetes Application</li></ul>
<p>
Developer), CKS (Certified Kubernetes Security Specialist), or CNPE (Certified Cloud Native Platform</p>
<p>
Engineer) are highly valued</p><br>
<p></p>
<p>
Experience</p>
<ul><li>Minimum of 2 years of relevant experience</li></ul></div></div><div></div>

AI/ML Support Automation Analyst

Sadat Consulting

<p><b>Sen your CV across mohammed.sadatgac@gmail.com with below details</b></p><p><b>1. Notice period</b><br/><b>2. Current salary</b><br/><b>3. Expected salary</b><br/><b>4. Do you have Transferable IQAMA</b></p><p><b>Role Purpose </b></p><p>Develop AI-enabled automation aligned with roadmap including automation workflows, AI</p><p>assisted reporting, anomaly detection, and enterprise AI integration patterns.</p><p>Key Responsibilities</p><ul><li>Develop automation pipelines and workflow automations</li><li>Integrate enterprise AI services (LLM APIs, automation endpoints)</li><li>Develop anomaly detection logic and operational intelligence rules</li><li>Build AI-assisted reporting components aligned with dashboards</li><li>Maintain AI/automation documentation and reproducibility</li><li>Ensure governance-aligned AI implementation (approval where required)</li><li>Support integration of AI outputs into enterprise apps (Frappe, dashboards)</li></ul><p>Mandatory Technical Requirements</p><ul><li>Python (ML/automation stack)</li><li>Experience integrating enterprise AI APIs</li><li>Familiarity with RAG architecture concepts</li><li>Automation frameworks and scripting (job scheduling, pipelines)</li><li>Strong integration skills (API-based orchestration)</li></ul><p>Minimum Experience</p><ul><li>8+ years experience</li><li>Proven delivery of AI/automation in enterprise environments</li></ul><p>Job Types: Full-time, Permanent</p><p>Work Location: In person</p>

AI Automation (LLMs, RAG) Engineer

DeepSource Technologies

<div><p>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.</p><p></p><p>
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.</p><p></p><p>
Key Responsibilities</p><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.<br>
</li></ul><br>
<br>
<p></p><b>Requirements</b><ul><li><br>
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><p></p>

AI Architect - Riyadh,KSA

Qualcomm

<div><h2 class="jobSectionHeader"><b>Company:
</b></h2>Qualcomm Middle East Information Technology Company LLC
<p></p><h2 class="jobSectionHeader"><b>Job Area:
</b></h2>Engineering Group, Engineering Group &gt; Software Engineering
<p></p><p><b>General Summary:
</b></p><p></p><div><div><p><b>About Us
</b></p></div><div><p>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 intelligent edge devices, next-generation computing platforms, and advanced AI solutions. Qualcomm&rsquo;s leadership in AI, high ‑ performance compute, and connectivity is driving innovation across cloud, edge, and data center environments - delivering scalable, power ‑ efficient platforms that power the next generation of intelligent infrastructure.<br>
</p></div><p></p><div><p><b>About the Role
</b></p></div><div><p>Qualcomm is seeking a <b>Machine Learning Operations &amp; Customer Support Engineer </b>within the Customer Engineering team to support strategic customers deploying AI inference workloads on advanced Qualcomm AI inference accelerator s . These accelerators utilize Qualcomm's expertise in hardware-accelerated AI to deliver high-performance, energy-efficient generative AI and computer vision inference solutions for modern data centers.
</p></div><p></p><div><p>This is a <b>customer-facing, production-critical role </b>focused on ensuring maximum system uptime, reliability, and performance, while resolving customer support cases within defined SLAs/KPIs. The role requires deep expertise across ML inference pipelines, systems troubleshooting , and data center operations, working closely with customers, internal engineering, and product teams.
</p></div><div><p>The i deal candidate will bring a strong foundation in ML model deployment, systems engineering, rack-scale management software, DevOps/ MLOps automation, and cross functional collaboration.<br>
</p></div><p></p><div><p><b>What You&rsquo;ll Do
</b></p></div><div><p><b>Customer Support &amp; SLA Ownership
</b></p></div><div><ul><li>Act as the primary technical escalation point for customer issues related to AI inference workloads
</li></ul></div><div><ul><li>Own end-to-end case management, ensuring resolution within agreed SLAs and KPIs
</li></ul></div><div><ul><li><p>Drive incident response, triage, and root cause analysis (RCA) .
</p></li></ul></div><div><ul><li><p>Provide timely and transparent communication to customers on issue status and resolution
</p></li></ul></div><div><ul><li><p>Maintain high levels of customer satisfaction and service reliability
</p></li></ul></div><p></p><div><p><b>Uptime, Reliability &amp; Operations
</b></p></div><div><ul><li><p>Ensure high availability and uptime of customer AI deployments (rack-scale systems)
</p></li></ul></div><div><ul><li><p>Monitor system health, performance metrics, and workload behavior
</p></li></ul></div></div><div><div><ul><li><p>Implement and manage failover, redundancy, and resiliency mechanisms
</p></li></ul></div><div><ul><li><p>Proactively identify risks and implement preventative actions
</p></li></ul></div><p></p><div><p><b>AI Inference Workload Support
</b></p></div><div><ul><li><p>Support deployment, optimization, and troubleshooting of ML inference pipelines
</p></li></ul></div><div><ul><li><p>Debug issues across model, runtime, system, and hardware layers
</p></li></ul></div><div><ul><li><p>Analyze model performance (latency, throughput, accuracy tradeoffs) in production
</p></li></ul></div><div><ul><li><p>Support frameworks such as PyTorch , TensorFlow, ONNX, and model conversion flows
</p></li></ul></div><div><ul><li><p>Assist in model optimization techniques (quantization, batching, compilation, runtime tuning)
</p></li></ul></div><p></p><div><p><b>System &amp; Infrastructure Engineering
</b></p></div><div><ul><li><p>Support bare-metal and virtualized environments for AI workloads
</p></li></ul></div><div><ul><li><p>Troubleshoot issues across Linux OS, drivers, firmware, and networking stack
</p></li></ul></div><div><ul><li><p>Support deployment and maintenance using Infrastructure as Code ( IaC ) and automation tools
</p></li></ul></div><div><ul><li><p>Work with DCIM tools and monitoring systems for infrastructure visibility
</p></li></ul></div><div><ul><li><p>Coordinate with hardware vendors for accelerator, server, and networking issues
</p></li></ul></div><p></p><div><p><b>Monitoring, Observability &amp; Automation
</b></p></div><div><ul><li><p>Implement and manage monitoring systems (logs, metrics, traces)
</p></li></ul></div><div><ul><li><p>Build dashboards for uptime, SLA adherence, performance, and utilization
</p></li></ul></div><div><ul><li><p>Automate repetitive operational tasks using scripts and workflows
</p></li></ul></div><div><ul><li><p>Establish and enforce runbooks and standard operating procedures (SOPs)
</p></li></ul></div><p></p><div><p><b>Cross-Functional Collaboration
</b></p></div></div><div><div><ul><li><p>Work closely with Customer Engineering, Product, Engineering, and Support teams
</p></li></ul></div><div><ul><li><p>Provide structured feedback to engineering for product improvements and defect resolution
</p></li></ul></div><div><ul><li><p>Support customer onboarding, deployment readiness, and operational handover
</p></li></ul></div><div><ul><li><p>Participate in customer reviews, escalations, and technical deep dives<br>
</p></li></ul></div><p></p><div><p><b>Required Qualifications
</b></p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science , Computer Engineering, Electrical Engineering, or related field
</p></li></ul></div><div><ul><li><p>10&ndash;15+ years of experience in ML operations, systems engineering, or customer support engineering
</p></li></ul></div><div><ul><li><p>Proven experience in customer-facing technical roles with SLA-driven support models
</p></li></ul></div><div><ul><li><p>Strong experience with AI/ML inference workloads in production environments
</p></li></ul></div><div><ul><li><p>Deep understanding of end-to-end ML inference pipelines
</p></li></ul></div><div><ul><li><p>Hands-on experience with Linux systems, system bring-up, drivers, and debugging tools
</p></li></ul></div><div><ul><li><p>Strong understanding of AI accelerator architecture and system bottlenecks
</p></li></ul></div><div><ul><li><p>Experience with model deployment, optimization, and performance tuning
</p></li></ul></div><div><ul><li><p>Experience with data center operations and rack-scale deployments
</p></li></ul></div><div><ul><li><p>Familiarity with bare-metal, virtualization, and containerization technologies (Docker, Kubernetes)
</p></li></ul></div><div><ul><li><p>Knowledge of networking concepts (TCP/IP, RDMA, storage systems)
</p></li></ul></div><div><ul><li><p>Experience with cloud and hybrid environments
</p></li></ul></div><div><ul><li><p>Experience with monitoring/observability tools (Prometheus, Grafana, ELK, etc.)
</p></li></ul></div><div><ul><li><p>Strong skills in incident management, RCA, and production operations
</p></li></ul></div></div><div><div><ul><li><p>Experience defining and tracking SLAs, KPIs, and operational metrics
</p></li></ul></div><div><ul><li><p>Proficiency in Python, Bash, or similar scripting languages
</p></li></ul></div><div><ul><li><p>Experience in automation, DevOps, and MLOps tooling
</p></li></ul></div><div><ul><li><p>Strong problem-solving and diagnostic skills
</p></li></ul></div><div><ul><li><p>Excellent communication and customer engagement skills
</p></li></ul></div><div><ul><li><p>Ability to operate in high-pressure, mission-critical environments
</p></li></ul></div><div><ul><li><p>High attention to detail with a focus on quality, reliability, and accountability
</p></li></ul></div><p></p><div><p><b>Preferred Qualifications
</b></p></div><div><ul><li><p>Experience with Qualcomm Cloud AI or similar AI accelerator platforms
</p></li></ul></div><div><ul><li><p>Experience supporting large-scale AI deployments (LLMs, CV pipelines, generative AI)
</p></li></ul></div><div><ul><li><p>Familiarity with inference runtimes ( TensorRT , ONNX Runtime, custom runtimes)
</p></li></ul></div><div><ul><li><p>Experience with CI/CD pipelines for ML deployment<br>
</p></li></ul></div><p></p><div><p><b>Why Join Qualcomm
</b></p></div><div><p>At Qualcomm, you&rsquo;ll work at the intersection of <b>AI silicon, system architecture, and real </b>‑ <b>world deployment </b>. You will engage directly with strategic customers, influence next ‑ generation AI data center platforms, and help define scalable, power ‑ efficient infrastructure for the AI era. This role provides a unique opportunity to shape both <b>technology direction and customer outcomes </b>, while working with world ‑ class engineering and product teams.
</p><p></p><p><b>What's on Offer
</b></p><p>Apart from working with great people, we offer the below:
</p><ul><li><p>Salary including housing &amp; transport allowance
</p></li><li><p>Stock (RSU's) and performance related bonus
</p></li><li><p>16 weeks fully paid Maternity Leave
</p></li><li><p>6 weeks fully paid Paternity Leave
</p></li><li><p>Employee stock purchase scheme
</p></li><li><p>Child Education Allowance
</p></li><li><p>Relocation and immigration support (if needed)
</p></li><li><p>Life and Medical Insurance
</p></li><li><p>Live+ Well Reimbursement for health and recreational membership fees
</p></li></ul></div></div><p></p><p><b>Minimum Qualifications:
</b></p><ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
</li></ul>OR
<br>
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
<br>
OR
<br>
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
<br>
<br>
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul><p></p><p>*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.
</p><p></p><div><p>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).
</p></div><p></p><p>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.
</p><p></p><p><b>To all Staffing and Recruiting Agencies </b>: 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.
</p><p></p><p>If you would like more information about this role, please contact Qualcomm Careers .</p></div>

ML Operations & Customer Support Engineer, Staff/Senior Staff level - Riyadh, KSA

Cisco

Meet the Team
<br>As a Solutions Engineer at Cisco, you will work closely with the Service Provider Sales team to identify the needs one of Cisco’s most strategic Service Provider accounts in Saudi Arabia, demonstrate Cisco solutions, and design tailored products that drive digital transformation. You will provide expert technical guidance focused on customer success and aligned outcomes, while enjoying the flexibility to handle your work in a way that delivers the best results for both the customer and your team. This role requires solution engineer who combines, Enterprise networking, Data Center architecture solutions with strong AI, automation capable of guiding customers toward fully autonomous, AI-driven networks.
<br><br>
Your Impact
<br>As a Solution Engineer, you will play a pivotal role in accelerating Cisco's leadership by acting as a trusted technical advisor and solution architect. Your expertise will be crucial in translating service provider objectives into comprehensive, impactful architecture and solution strategies across Cisco’s diverse portfolio. Serve as the technical lead within the account team, building trusted advisor relationships with senior IT and business leaders.
<br><br>
<ul>
<li>Own the end-to-end technology vision and architecture, spanning Service Provider networks, Data Center, Cloud, Automation, Cybersecurity and AI driven operations.</li>
<li>Lead the design of large-scale, highly scalable Data Center, Enterprise Networking architectures, aligned with future autonomous networking models.</li>
<li>Lead AI-driven network transformation initiatives, including:</li>
<li>Applying AI/ML and LLM models to network operations, assurance, planning, and optimization</li>
<li>Positioning Agentic AI for closed-loop decision making, intent execution, and self-healing networks</li>
<li>Integrating AI capabilities across transport, Data Center, cloud and cybersecurity domains</li>
<li>Articulate and demonstrate the business impact of AI on network efficiency, cost optimization, resilience, and customer experience.</li>
<li>Lead network automation and orchestration strategy, with deep expertise in DNA Center, Nexus Dashboard, Cisco Intersight and Cisco Crosswork Automation portfolio</li>
<li>Collaborate with account teams, product leaders, and executives to influence roadmaps, investment decisions, and long-term transformation strategy.</li>
<li>Develop and present high-impact technical proposals, architectures, and demonstrations.</li>
<li>Drive proof of concepts (POCs), pilots, and solution validation to accelerate decision-making and adoption.</li>
</ul>
Minimum Qualifications
<br><br>
<ul>
<li>3+ year’s of proven experience in presales, consultative, or solution architect roles, demonstrating a proven presales track record in designing and deploying solutions, particularly in routing, switching, data center and cloud.</li>
<li>Technical expertise in:</li>
<li>Scalable, AI-ready Data Center architecture including compute, storage solutions (Cisco or 3rd party), data center networking, Cisco ACI</li>
<li>Enterprise network architectures using Cisco routing, switching and wireless solutions, SD-WAN, SASE, modern AI Ops/ML Ops, and programming/scripting capabilities.</li>
<li>Service provider network architecture spanning Access, transport, Data center, and Internet with related technologies.</li>
<li>Strong AI and automation expertise, including:</li>
<li>Applied understanding of AI/ML models for networking use cases such as assurance, optimization, planning, and predictive operations</li>
<li>Architectural or hands-on knowledge of LLM-based systems for operational insights, automation, and decision support</li>
<li>Experience designing or positioning Agentic AI frameworks to enable closed-loop, intent-based, and autonomous network operations</li>
<li>Strong understanding of Cisco technologies and architecture, with proven cross-architecture experience to translate client objectives into comprehensive solutions across Cisco’s full portfolio.</li>
<li>Ability to simplify complex technical concepts for both technical and non-technical audiences, coupled with strong executive-level communication skills.</li>
<li>Solid experience engaging directly with customers, applying consultative selling techniques, understanding financial pain points, and aligning solutions with customer business models to drive value realization and adoption.</li>
</ul>
Preferred Qualifications
<br><br>
<ul>
<li>Bachelor’s degree in electrical engineering, Computer Science, or a related field.</li>
<li>Cisco certifications (e.g., CCNA, CCNP, CCIE) or equivalent vendor credentials.</li>
<li>Experience in Enterprise networking solutions: campus and branch, secure network architecture, access, wireless, wide area network, visibility and monitoring solutions</li>
<li>Understanding of data center technologies: hyperconverged infrastructure, cloud computing and networking, Data center fabric, servers, unified edge, SDN controller,</li>
<li>High level understanding of Service Provider Routing and Transport, including SR-MPLS and SRv6, Mobility, 5G Core network design and evolution</li>
<li>Ability to work effectively, add value as a team member, and assume a proactive approach to your career, demonstrating a growth mindset and adaptability.</li>
<li>Excellent written and verbal communication, listening, and strong presentation skills.</li>
<li>Experience in Saudi Arabia market is highly desirable, with Arabic language proficiency considered a significant plus.</li>
</ul>
<b>Nature of the Work:</b> Hybrid Full Time
<br><b>Hours of work:</b> 48 hours per week
<br><b>Benefits:</b> Healthcare and Insurance, Employee Stock Purchase program, Flexible Spending Benefit, Flex and Schooling Allowances and many more.
<br><b>Application start and end date:</b> Starting 6th of May for approx. 4-6 weeks
<br><br>
Why Cisco?
<br><br>
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
<br>Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
<br>We are Cisco, and our power starts with you.

Solutions Engineer

Talent 360

<div><p><b>About Us</b></p><p><br>
We are building the next-generation Office of the CFO that simplifies finance for all businesses.</p><p><br>
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.</p><p><br>
As we scale, trusted data becomes core infrastructure powering financial correctness, operational visibility, and AI-powered automation.</p><p><b><br>
About the Role</b></p><p><br>
We are looking for a Senior Data Engineer to help define and scale the foundation of SiFi&rsquo;s data platform.</p><p><br>
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.</p><p><br>
This is a high-ownership role focused on building financial data infrastructure from first principles.</p><p><br>
This role is based in Saudi Arabia (Relocation).</p><p><b><br>
What You Will Own</b></p><p><b><br>
Data Modeling and Standards</b></p><br>
<ul><li>
Define and maintain scalable data models in SQL<br>
</li><li>
Establish structured warehouse layers and modeling best practices<br>
</li><li>
Own KPI definitions and ensure a single source of truth<br>
</li><li>
Ensure financial correctness and metric consistency</li></ul><p><b><br>
Warehouse Architecture</b></p><br>
<ul><li>
Design and evolve our cloud data warehouse in BigQuery<br>
</li><li>
Own transformation workflows using dbt, SQLMesh, or similar tools<br>
</li><li>
Optimize performance, reliability, and cost<br>
</li><li>
Design and support production-grade AI/ML pipelines ensuring model performance, data integrity, and compliance.</li></ul><p><b><br>
Reliability and Governance</b></p><br>
<ul><li>
Ensure data quality, integrity, and observability<br>
</li><li>
Implement access controls aligned with compliance requirements<br>
</li><li>
Build a scalable foundation ready for advanced analytics and AI</li></ul><p><b><br>
Cross-Functional Impact</b></p><br>
<ul><li>
Translate business requirements into robust data systems<br>
</li><li>
Enable trusted reporting and BI across teams<br>
</li><li>
Support experimentation and AI-driven initiatives with well-structured datasets</li></ul><br>
<b>
Requirements</b><p><b><br>
What We Are Looking For</b></p><br>
<ul><li>
5+ years of experience in Data Engineering or Analytics Engineering<br>
</li><li>
Strong SQL expertise with hands-on data modeling experience<br>
</li><li>
Experience with cloud data warehouses such as BigQuery<br>
</li><li>
Experience with modern transformation frameworks such as dbt or SQLMesh<br>
</li><li>
Experience building or supporting production-grade AI/ML pipelines is a strong plus<br>
</li><li>
Ability to operate independently in a fast-moving startup<br>
</li><li>
Operates with high agency, taking end-to-end ownership of complex problems and delivering outcomes</li></ul></div>

Senior AI Data Engineer

Tamer Group

<div>
 <p>
  <strong>
   Job Purpose:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are currently seeking a Senior Data Analyst / Sr. Business Intelligence Analyst to support business decision-making through data analysis, reporting, and business intelligence solutions.
 </p>
 <p>
  The ideal candidate should have solid experience in Data Analytics, Business Intelligence, Data Visualization, and Reporting, with strong hands-on expertise in Power BI, SQL, Data Modeling, and KPI analysis.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Design, develop, and maintain interactive Power BI dashboards and reports across multiple business functions, including Finance, Procurement, Supply Chain, and Sales.
  </li>
  <li>
   Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and business opportunities.
  </li>
  <li>
   Translate business requirements into analytical frameworks and actionable insights.
  </li>
  <li>
   Support data collection, preparation, validation, and quality assurance activities.
  </li>
  <li>
   Develop and maintain data models, measures, and calculations using DAX and Power Query (M).
  </li>
  <li>
   Collaborate with business stakeholders, IT teams, and BI teams to ensure data integrity, reporting accuracy, and alignment with business KPIs.
  </li>
  <li>
   Support Business Intelligence initiatives, reporting optimization, and self-service BI adoption.
  </li>
  <li>
   Utilize AI-enabled analytics capabilities within Microsoft Fabric and Power BI, including Copilot and Natural Language Query features, while validating analytical outputs for business relevance and accuracy.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Information Technology, Data Science, Statistics, or a related field.
  </li>
  <li>
   4&ndash;7 years of experience in Data Analysis, Business Intelligence, Reporting, or related IT functions.
  </li>
  <li>
   Advanced proficiency in Power BI, including Dashboards, Dataflows, Datasets, DAX, Power Query, and Report Development.
  </li>
  <li>
   Strong experience in SQL querying, relational databases, and data warehouses.
  </li>
  <li>
   Experience in Data Modeling, ETL/Data Preparation, KPI Reporting, and Data Visualization.
  </li>
  <li>
   Familiarity with Microsoft Fabric (Lakehouse, OneLake, Data Pipelines, Data Warehouse) is preferred.
  </li>
  <li>
   Exposure to AI-assisted analytics tools, reporting automation, and advanced analytics capabilities is an advantage.
  </li>
  <li>
   Certifications such as PL-300 (Microsoft Certified: Power BI Data Analyst Associate) are preferred; DP-600 (Microsoft Fabric Analytics Engineer Associate) is a plus.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Candidates with relevant experience in Power BI, SQL, Business Intelligence, Data Analytics, Data Visualization, Microsoft Fabric, DAX, Power Query, Data Modeling, and KPI Reporting are encouraged to apply.
 </p>
</div>


Senior Data Analyst

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