Head of Infrastructure, ADASAD

About Lucid

At Lucid we are creating exceptional mobility experiences through innovation to drive the world forward. Built on Lucids proprietary technology and software-defined vehicle architecture our award-winning vehicles bring our Compromise Nothing approach to the global automotive market. That means refusing to choose between performance and sustainability design and engineering ambition and Lucid Air and Lucid Gravity we have designed and built vehicles that have redefined their segments combining exceptional range performance design and expansive space in a single experience.

We achieve this through deep vertical integration with design engineering and productionhappening in-houseacross our global offices the world united by a shared commitment to refusing to settle youcanhelpredefinewhatspossible andshape the future of mobility.

The Head of Infrastructure ADAS / Autonomous Driving is a senior leadership role responsible for designing building and operating scalable cloud and hybrid infrastructure to support ADAS and autonomous vehicle product delivery. This role owns the endtoend infrastructure architecture including cloud strategy security models DevOps practices CI/CD and ML pipelines and data governance for global deployments.

This is a handson builderfocused role. The successful candidate will establish and grow an inhouse DevOps and infrastructure organization define internal versus vendor ownership boundaries and architect systems that enable reliable secure costefficient and compliant development of production ADAS and autonomous vehicle software. Success requires deep technical expertise strong leadership and experience operating in fastmoving startup or growth environments.

• Own and define the endtoend infrastructure and security architecture across cloud on-premises and hybrid environments.
• Design deploy and operate scalable cloud infrastructure and largescale data pipelines supporting sensor data ingestion ML training simulation validation and deployment for ADAS and autonomous vehicle systems.
• Lead efforts to modernize optimize and improve cost efficiency and performance of legacy infrastructure and data/ML pipelines including identifying opportunities for architectural simplification and automation.
• Build and own CI/CD and ML pipelines supporting production AI and software workflows with an emphasis on reliability scalability and efficiency.
• Implement InfrastructureasCode and automation frameworks for secure repeatable deployments.
• Manage cloud infrastructure across AWS OCI Azure or similar platforms including access control cost governance and resource optimization.
• Define ownership boundaries and partner effectively with IT and external vendors while retaining architectural control.
• Improve developer productivity and system reliability through tooling observability automation and standardized development workflows.
• Ensure infrastructure and data platforms align with data privacy security and regional compliance requirements including GDPR and regionspecific constraints for the EU KSA and other global markets.
• Define and track KPIs for reliability scalability cost efficiency and developer experience.
• Collaborate crossfunctionally with Software Product Systems Validation Program and Operations teams.
• Evaluate and adopt emerging infrastructure DevOps MLOps and AIenabled tools where they provide clear value.

• Handson experience designing and operating cloud infrastructure architectures (AWS OCI Azure or similar).
• Proven experience standing up and leading an inhouse DevOps or infrastructure organization.
• Strong experience with CI/CD pipelines and production ML workflows.
• Deep knowledge of InfrastructureasCode and automation tools such as Terraform and GitOps.
• Experience operating in hybrid environments (onpremises and cloud).
• Experience working on cost optimization performance tuning and modernization of largescale or legacy infrastructure and data pipelines.
• Practical understanding of data privacy security and regulatory considerations including experience handling data in regulated environments (e.g. GDPR EU Middle East/KSA).
• Builder mindset with experience in startup or growthstage environments.
• Experience supporting AIheavy dataintensive or realtime systems.
• Strong leadership communication and crossfunctional collaboration skills.
• Ability to independently design validate and defend infrastructure and security decisions.

• Experience across multiple areas of AI such as machine learning platforms data engineering perception systems or MLOps beyond core infrastructure responsibilities.
• Platform software middleware or SDK development experience.
• Background in ADAS autonomous vehicles robotics medical devices or other safetycritical domains.
• Experience with autonomous vehicle systems and physical sensor data such as cameras LiDAR radar or GPS.
• Proficiency with containerized infrastructure and orchestration ecosystems including Kubernetes Docker and Helm as well as MLOps platforms and observability tooling.
• Familiarity with functional safety or automotive standards such as ISO 26262 ASPICE or SOTIF.
• Cloud DevOps or Kubernetes certifications.

• Bachelors degree in Computer Science Software Engineering Information Technology or a related technical field.
• Masters degree preferred.