sales engineer

qa/qc engineer

procurement engineer

project engineer

qa engineer

ai ml engineer

YO IT Consulting

<div>
 
 Job Title:
 
 AI/ML Engineer
 
 
 
 Job Type:
 
 Full-Time
 
 
 
 Job Summary
 
 
 
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
 </li>
 <li>
 Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
 </li>
 <li>
 Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
 </li>
 <li>
 Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
 </li>
 <li>
 Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
 </li>
 <li>
 Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
 </li>
 <li>
 Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
 </li>
 <li>
 Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
 </li>
 <li>
 Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
 </li>
 <li>
 Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
 </li>
 <li>
 Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
 </li>
 <li>
 Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
 </li>
 <li>
 Exceptional written and verbal communication skills for effective collaboration and documentation.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
 </li>
 <li>
 Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
 </li>
 <li>
 Prior exposure to government or highly regulated cloud environments and compliance standards.
 </li>
 </ul>
</div>

AI/ML Engineer - Remote

Qualcomm

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Software Test Engineering
General Summary:
About Us
<div>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.
</div>About the Role
We are looking for a Site Reliability Engineer or Senior Engineer &ndash; Datacentre AI Engineering at Qualcomm Technologies, Inc., located in Riyadh, Saudi Arabia.
The role focuses on the design, operation, and continuous improvement of large‑scale AI inference systems in a datacenter environment. The engineer will support critical AI use cases by ensuring Qualcomm&rsquo;s AI infrastructure is reliable, scalable, and production‑ready for advanced machine‑learning workloads.
The role requires strong systems and software engineering fundamentals, hands‑on execution, and the ability to work independently on complex problem areas while collaborating closely with cross‑functional teams across hardware, software, and machine learning.
Ideal candidates will have 2-8 years of experience
Key Responsibilities will include
Key Responsibilities
1. AI Infrastructure
<ul><li>Design, deploy, and operate large‑scale AI inference systems supporting critical AI workloads.
</li><li>Ensure reliability, availability, and scalability of Qualcomm datacenter AI clusters.
</li><li>Develop and maintain software tools and support infrastructure around AI software stacks.
</li></ul>2. AI &amp; ML Engineering
<ul><li>Analyze software requirements and collaborate with architecture and hardware engineers to support AI workloads.
</li><li>Build, deploy, and operate components supporting LLM inference, agentic AI workflows, and AI services.
</li><li>Work with models, systems, and software teams to improve model performance on AI100 deployments.
</li><li>Identify and implement optimizations for workloads running on multi‑SoC and multi‑card systems.
</li></ul>3. Site Reliability Engineering (SRE)
<ul><li>Apply SRE fundamentals including monitoring, alerting, incident response, and performance optimization.
</li><li>Support production ML systems using MLOps tools and operational best practices.
</li><li>Contribute to incident reviews, operational documentation, and continuous reliability improvements.
</li></ul>4. Observability &amp; Tooling
<ul><li>Build and maintain observability tools, dashboards, and alerts to monitor system health and reliability.
</li><li>Monitor infrastructure and services using tools such as Prometheus, Grafana, CloudWatch, and custom telemetry.
</li><li>Create and maintain technical documentation, runbooks, and knowledge‑base articles.
</li></ul>5. Automation &amp; CI/CD
<ul><li>Develop automation to reduce manual operational tasks and improve system reliability.
</li><li>Support CI/CD pipelines for AI service and agent deployment.
</li><li>Apply Infrastructure‑as‑Code practices using tools such as Terraform and Ansible.
</li></ul><div></div>Required Skillset
1. AI &amp; Deep Learning
<ul><li>Experience working with AI/ML workloads such as LLMs, NLP, Vision, Audio, or Recommendation systems.
</li><li>Understand ML inference concepts including batching, token streaming, and performance considerations.
</li><li>Hands‑on experience with PyTorch and familiarity with modern ML frameworks.
</li><li>Familiarity with distributed inference, checkpointing, and accelerator‑based compute environments.
</li></ul>2. AI Operations
<ul><li>Experience supporting AI or ML applications in production environments.
</li><li>Familiarity with LLM inference pipelines and AI service operations.
</li></ul>3. Programming &amp; Software Design
<ul><li>Strong programming skills in Python with experience building and supporting production systems.
</li><li>Experience with scripting and automation using Python and Bash.
</li><li>Familiarity with configuration management and orchestration tools.
</li></ul>4. Systems &amp; Infrastructure
<ul><li>Strong Linux fundamentals include shell, containers, system services, and networking basics (DNS, TLS, HTTP/gRPC).
</li><li>Experience working with cluster schedulers such as Slurm or equivalent systems.
</li><li>Experience operating distributed systems with high availability and fault tolerance.
</li></ul>5. Observability &amp; Monitoring
<ul><li>Hands‑on experience with monitoring and logging tools such as Prometheus, Grafana, ELK, or Loki.
</li><li>Understanding of incident management, service health metrics, and system reliability monitoring.
</li></ul>6. DevOps &amp; SRE Practices
<ul><li>Solid understanding of SDLC, release processes, and operational reliability practices.
</li><li>Familiarity with CI/CD pipelines and Infrastructure‑as‑Code tools.
</li></ul><div></div>Preferred Skillset
<ul><li>Experience with GenAI, Agentic AI systems, or LLM orchestration frameworks.
</li><li>Exposure to LangChain, AutoGen, or RAG‑based systems.
</li><li>Experience with additional ML frameworks such as TensorFlow, JAX, or Ray.
</li><li>Knowledge of GPU/accelerator‑based systems and high‑performance networking (RDMA, InfiniBand, RoCE).
</li><li>Experience with advanced MLOps workflows or large‑scale AI platform operations.
</li></ul><div></div>Qualifications
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in engineering, Computer Science, AI/ML, or a related field.
</li><li>2&ndash;8 years of software, systems, or infrastructure engineering experience, preferably in production or datacenter environments.
</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 4+ years of Software Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul>*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.
<div>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).
</div>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>

Infrastructure & Site Reliability Engineer – Datacentre AI Engineering - Riyadh, KSA

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Systems Engineering
General Summary:
<div></div><div>About Us
</div><div>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.
</div><div></div><div>About the Role
</div><div>As a Qualcomm Datacenter AI Solutions Engineer, you will research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine learning solutions that enable the deployment of cutting-edge AI datacenter technology.
Qualcomm Solution Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is a great opportunity to innovate and develop leading-edge products and solutions around best-in-class Qualcomm AI inference accelerators for data center, and hybrid AI applications.
Principal Duties and Responsibilities:
<ul><li>Design, develop, and optimize AI/ML solutions leveraging Qualcomm AI hardware, software, and ecosystem to deliver high-performance, power‑efficient, and scalable inference
</li><li>Develop and deploy GenAI and LLM-based applications, including model integration, fine-tuning, and optimization
</li><li>Apply systems-level knowledge to analyze, design, implement, and validate AI software, models, and system architecture
</li><li>Perform AI model benchmarking, functional analysis, and performance characterization to drive requirements and improvements
</li><li>Support customer engagements by optimizing AI models and workloads for deployment and inference efficiency
</li><li>Contribute to system-level design efforts, including requirements definition, interfaces, performance targets, and implementation
</li><li>Collaborate closely with cross-functional teams to implement, test, and validate AI system features
</li><li>Debug and triage system-level issues, perform root-cause analysis, and communicate findings clearly
</li><li>Stay current with advancements in AI/ML models, tools, and hardware, and apply innovative ideas to products and solutions
</li></ul>Preferred Qualifications:
<ul><li>Master&rsquo;s or PhD in Engineering, Computer Science, Information Systems, or a related field
</li><li>Proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture
</li><li>Hands-on experience building, deploying, and tuning AI/ML systems
</li><li>Strong understanding of GenAI architectures (e.g., transformers, diffusion models, LLMs, embeddings)
</li><li>Experience with large-scale AI system design, including distributed systems, fault tolerance, and event-driven architectures
</li><li>Familiarity with MLOps practices and ML lifecycle management
</li><li>Experience with containerization and automation tools (Docker, Kubernetes, Git/GitOps)
</li><li>Experience with model fine-tuning and/or reinforcement learning is a plus
</li><li>Familiarity with observability, benchmarking, and performance analysis for ML pipelines is a plus
</li><li>Experience working in large, matrixed organizations and collaborating across teams
</li><li>Strong problem-solving skills and customer-focused mindset
</li><li>Experience with open-source development practices
</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></div>Minimum Qualifications:
<ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field.
*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.
<div>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).
</div>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>

Datacenter AI Solutions Engineer - Riyadh, KSA

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Systems Engineering
General Summary:
About Us
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
As a Qualcomm Datacenter AI Solutions Engineer, you will research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine learning solutions that enable the deployment of cutting-edge AI datacenter technology.
Qualcomm Solution Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is a great opportunity to innovate and develop leading-edge products and solutions around best-in-class Qualcomm AI inference accelerators for data center, and hybrid AI applications.
We are looking for Engineers with 8+ years of experience
Principal Duties and Responsibilities:
<ul><li>Lead the development of end-to-end AI/ML solutions that integrate Qualcomm AI hardware, system software, and ecosystem components to deliver best-in-class AI inference performance, power efficiency, and scalability
</li><li>Drive the design, development, deployment, and optimization of Generative AI and LLM-based applications, with a focus on production readiness and inference efficiency
</li><li>Contribute to and guide the implementation of model fine-tuning, distillation, and optimization strategies tailored for deployment on target hardware
</li><li>Apply deep systems-level expertise to research, design, develop, simulate, validate, and optimize AI systems spanning hardware, system software, AI frameworks, and models, while ensuring system-level requirements are met
</li><li>Perform AI model benchmarking, workload characterization, and performance analysis to influence system requirements, hardware/software co-design, and product direction
</li><li>Serve as a technical lead for customer engagements, supporting AI model onboarding, inference optimization, deployment, and performance tuning
</li><li>Own and drive system-level architecture and design, including requirements definition, interface specifications, performance targets, and implementation of new systems or enhancements to existing platforms
</li><li>Collaborate across cross-functional teams (hardware, software, tools, frameworks, and product) to deliver features, validate AI system correctness, and ensure high-quality execution
</li><li>Stay current with advancements in AI/ML models, inference techniques, and hardware/software innovations, and proactively translate them into impactful solutions
</li><li>Propose and drive new, innovative ideas that meaningfully improve products, platforms, or developer experience
</li><li>Lead system-level debugging and triage, identify root causes across the stack, and clearly communicate findings, trade-offs, and recommendations to team members and stakeholders
</li></ul>Preferred Qualifications &amp; Skills:
<ul><li>Master&rsquo;s or PhD in Engineering, Computer Science, Information Systems, Physics, or a related discipline
</li><li>Strong proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture
</li><li>Hands-on experience designing, deploying, and operating AI/ML systems in production
</li><li>Solid understanding of Generative AI architectures, including transformers, diffusion models, and hybrid systems (LLMs, LVMs, embeddings)
</li><li>Experience with large-scale AI systems architecture, including microservices, distributed systems, event-driven designs, and fault-tolerant/resilient architectures
</li><li>Practical experience with AI inference serving, performance optimization, and scalability across heterogeneous hardware
</li><li>Experience with MLOps practices for AI application development, deployment, monitoring, and lifecycle management
</li><li>Familiarity with automation and DevOps tooling, including GitOps workflows, containerization (Docker), orchestration platforms (Kubernetes), and ML lifecycle tools
</li><li>Strong problem-solving skills with a customer- and solution-focused mindset
</li><li>Experience with cluster schedulers and resource managers (e.g., Slurm, PBS) and workload orchestration is a plus
</li><li>Experience with observability, monitoring, and debugging tools for ML pipelines and inference services
</li><li>Proven ability to operate effectively in a large, matrixed organization, influencing across teams
</li><li>Experience with fine-tuning and optimization of GenAI models, including reinforcement learning techniques, is a plus
</li><li>Well versed in open-source development practices, collaboration, and code quality standards
</li><li>Exposure to rack-level orchestration, fleet management, and data center automation is a plus
</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 4+ years of Systems Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
*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.
<div>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).
</div>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>

System level AI Solutions & Software Engineer (Staff level) - Riyadh, KSA

<div><div>We help the world run better 
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div> 
What you'll build 
You will work with customers, identify high‑impact AI use cases in their SAP landscape, and build end‑to‑end solutions in close collaboration with multiple roles at SAP within product &amp; engineering and customer services &amp; delivery. 
You will: 
<ul><li>
Work directly with Public Sector customers in KSA to discover, prioritize, and frame AI use cases on top of S/4HANA and SAP BTP.
</li><li>Design and implement end‑to‑end AI solutions: data pipelines from SAP, model selection/integration (SAP Business AI / BTP services), and UI/process integration.
</li>Run agile cycles (PoC pilot<li> production), gather user feedback, and drive adoption in real business processes.
</li><li>Act as the &ldquo;bridge&rdquo; between Riyadh Lab customers and global SAP Product &amp; Engineering, feeding requirements, gaps, and patterns into the roadmap.
</li>Produce reusable accelerators (reference architectures, templates, best practices) that can be scaled across KSA and the region. 
<li>
</li></ul>What you bring 
You are able to translate business challenges into clear technical designs and deliver end‑to‑end, production‑ready solutions. You are confident working directly with customers, leading discovery sessions, delivering demos, and explaining technical trade‑offs in business terms. You are comfortable operating in a forward‑deployed role, taking ownership, collaborating closely with global teams, and staying motivated by creating real, measurable impact for customers. Experience working with local customers and partners is a plus. 
In a nutshell &ndash; you have: 
<ul><li>
Usually 10+ years of professional experience</li><li>
Solid grounding in data and AI/ML concepts (data modelling, APIs, common AI patterns such as forecasting, classification, copilots/assistants).</li><li>
End to End process knowledge of fundamental Public Sector processes such as Budget Planning, Budget Execution, Grants Management or Funds Management.</li><li>
Knowledge of the Public Sector market, its evolution, industry-specific challenges and SAP&rsquo;s industry portfolio</li><li>
Confidence in customer‑facing work and partner-facing work: discovery workshops, demos, handling challenging stakeholders, and explaining technical trade‑offs in business language.</li><li>
Software engineering background (e.g., Python/Java/TypeScript) plus hands‑on experience with SAP BTP, integrations, and at least one major SAP domain (finance, logistics, HR, public sector).</li><li>
Prototyping skills with tools like Claude Code or FIGMA.</li><li>
Fluent professional proficiency in English and Arabic, both written and spoken (as a must).</li></ul> 
And you are: 
<ul><li>
Comfortable operating like a &ldquo;forward‑deployed&rdquo; engineer: high ownership, ambiguity‑tolerant, collaborative with global teams, and motivated by real impact at customers.</li></ul> 
Where you belong 
You will be part of a growing AI and industry expert team dedicated to serving customers across the KSA. We are building a collaborative, high impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets. 
This team thrives working together on fast-paced projects to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real world impact matters. 
This is a place for people who enjoy building something new. You will thrive here if you are customer centric, motivated by meaningful outcomes, and comfortable navigating fast evolving AI landscape.<div> 
Bring out your best 
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
 
 
We win with inclusion 
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world. 
 
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com. 
 
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. 
 
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements. 
 
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div> 
AI Usage in the Recruitment Process</div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div>Please note that any violation of these guidelines may result in disqualification from the hiring process. 
 
Requisition ID: 450203 | Work Area: Solution and Product Management | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

AI (Chief-) Product Expert for Public Sector

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. 
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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>

Senior Ai Engineer - Riyadh,KSA

Master Works

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 This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
 
 
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 Design, develop, train, and optimize machine learning models for real applications or use cases
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 Translate business and product requirements into scalable ML/AI solutions.
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 Implement feature engineering, model selection, tuning, and evaluation techniques.
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 Develop , and deploy ML models into production environments with high availability and performance
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 Build and maintain ML pipelines (training, validation, deployment, monitoring).
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 Monitor model performance, data drift, and model decay; retrain models as needed.
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 Ensure models meet reliability, scalability, and security standards.
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 Work closely with Data Scientists, Product Managers, and Software Engineers.
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 Collaborate with data engineering teams to ensure high-quality, reliable data pipelines
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 Participate in design and code reviews, ensuring engineering best practices.
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 Optimize models for latency, throughput, and cost.
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 Implement experimentation frameworks (A/B testing, offline evaluation).
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 Apply responsible AI principles, including fairness, explainability, and governance where required
 
 
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 Requirements
 
 
 
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 3-7+ years of hands-on experience in Machine Learning or applied AI roles
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 Strong programming skills in Python (and/or Java, Scala).
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 Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
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 Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
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 Experience deploying models using Docker, Kubernetes, or cloud ML services.
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 Strong knowledge of data structures, algorithms, and software engineering principles.
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 Experience working in agile, cross-functional teams
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 Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
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 Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
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 Experience with big data technologies (Spark, Kafka, Databricks).
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 Background in NLP, Computer Vision, or Generative AI.
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 Strong problem-solving and analytical thinking
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 Production-first mindset
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 Data-driven decision making
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 High Collaboration and communication skills
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AI Engineer

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