Senior Staff / Principal Software Architect – System Level Datacenter AI Platforms - Riyadh, KSA
Qualcomm
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Benefits offered by this job
Job summary
Qualcomm Middle East Information Technology Company LLC is expanding in Riyadh and seeks Data Centre Engineers to advance AI/ML infrastructure for secure, scalable data center operations. You will research, develop, and optimize software, hardware, and architectures to deploy cutting-edge AI inference at scale, collaborating with cross-functional teams to meet performance and reliability targets.
The role emphasizes production readiness, deployment optimization, and continual learning to stay
Qualifications
- Bachelor's degree in Engineering, Computer Science, Information systems or related field and 12+ years of related work experience.
- Master's degree in Engineering, Computer Science, Information systems or related field and 10+ year of related work experience.
- PhD in Engineering, Computer Science, or related field and 8 years of experience
- Strong proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture
- Hands-on experience designing, deploying, and operating AI/ML systems in production
- Solid understanding of Generative AI architectures, including transformers, diffusion models, and hybrid systems (LLMs, LVMs, embeddings)
- Experience with large-scale AI systems architecture, including microservices, distributed systems, event-driven designs, and fault-tolerant/resilient architectures
- Practical experience with AI inference serving, performance optimization, and scalability across heterogeneous hardware
- Experience with MLOps practices for AI application development, deployment, monitoring, and lifecycle management
- Familiarity with automation and DevOps tooling, including GitOps workflows, containerization (Docker), orchestration platforms (Kubernetes), and ML lifecycle tools
- Strong problem-solving skills with a customer-and solution-focused mindset
- Experience with cluster schedulers and resource managers (e.g., Slurm, PBS) and workload orchestration is a plus
- Experience with observability, monitoring, and debugging tools for ML pipelines and inference services
- Proven ability to operate effectively in a large, matrixed organization, influencing across teams
- Experience with fine-tuning and optimization of GenAI models, including reinforcement learning techniques, is a plus
- Well versed in open-source development practices, collaboration, and code quality standards
- Exposure to rack-level orchestration, fleet management, and data center automation is a plus
Responsibilities
- 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
- Drive the design, development, deployment, and optimization of Generative AI and LLM-based applications, with a focus on production readiness and inference efficiency
- Contribute to and guide the implementation of model fine-tuning, distillation, and optimization strategies tailored for deployment on target hardware
- 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
- Perform AI model benchmarking, workload characterization, and performance analysis to influence system requirements, hardware/software co-design, and product direction
- Serve as a technical lead for customer engagements, supporting AI model onboarding, inference optimization, deployment, and performance tuning
- 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
- Collaborate across cross-functional teams (hardware, software, tools, frameworks, and product) to deliver features, validate AI system correctness, and ensure high-quality execution
- Stay current with advancements in AI/ML models, inference techniques, and hardware/software innovations, and proactively translate them into impactful solutions
- Propose and drive new, innovative ideas that meaningfully improve products, platforms, or developer experience
- 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
Skills
Education
Tools
Job description
Qualcomm Middle East Information Technology Company LLC
Engineering Group, Engineering Group > Systems Engineering
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. As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next‑generation experiences and drives digital transformation to help create a smarter, connected future for all. 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.
- Bachelor's degree in Engineering, Computer Science, Information systems or related field and 12+ years of related work experience.
- Master's degree in Engineering, Computer Science, Information systems or related field and 10+ year of related work experience.
- PhD in Engineering, Computer Science, or related field and 8 years of experience
- Strong proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice‑based architecture
- Hands‑on experience designing, deploying, and operating AI/ML systems in production
- Solid understanding of Generative AI architectures, including transformers, diffusion models, and hybrid systems (LLMs, LVMs, embeddings)
- Experience with large‑scale AI systems architecture, including microservices, distributed systems, event‑driven designs, and fault‑tolerant/resilient architectures
- Practical experience with AI inference serving, performance optimization, and scalability across heterogeneous hardware
- Experience with MLOps practices for AI application development, deployment, monitoring, and lifecycle management
- Familiarity with automation and DevOps tooling, including GitOps workflows, containerization (Docker), orchestration platforms (Kubernetes), and ML lifecycle tools
- Strong problem‑solving skills with a customer‑and solution‑focused mindset
- Experience with cluster schedulers and resource managers (e.g., Slurm, PBS) and workload orchestration is a plus
- Experience with observability, monitoring, and debugging tools for ML pipelines and inference services
- Proven ability to operate effectively in a large, matrixed organization, influencing across teams
- Experience with fine‑tuning and optimization of GenAI models, including reinforcement learning techniques, is a plus
- Well versed in open‑source development practices, collaboration, and code quality standards
- Exposure to rack‑level orchestration, fleet management, and data center automation is a plus
- 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
- Drive the design, development, deployment, and optimization of Generative AI and LLM‑based applications, with a focus on production readiness and inference efficiency
- Contribute to and guide the implementation of model fine‑tuning, distillation, and optimization strategies tailored for deployment on target hardware
- 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
- Perform AI model benchmarking, workload characterization, and performance analysis to influence system requirements, hardware/software co‑design, and product direction
- Serve as a technical lead for customer engagements, supporting AI model onboarding, inference optimization, deployment, and performance tuning
- 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
- Collaborate across cross‑functional teams (hardware, software, tools, frameworks, and product) to deliver features, validate AI system correctness, and ensure high‑quality execution
- Stay current with advancements in AI/ML models, inference techniques, and hardware/software innovations, and proactively translate them into impactful solutions
- Propose and drive new, innovative ideas that meaningfully improve products, platforms, or developer experience
- 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
- Salary including housing & transport allowance
- Stock (RSU's) and performance related bonus
- 16 weeks fully paid Maternity Leave
- 6 weeks fully paid Paternity Leave
- Employee stock purchase scheme
- Child Education Allowance
- Relocation and immigration support (if needed)
- Life and Medical Insurance
- Live+ Well Reimbursement for health and recreational membership fees
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
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.
Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disability‑accomodations@qualcomm.com or call Qualcomm's toll‑free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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.
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