Cloud DevOps and AI Security Engineer

Renesas Electronics is an embedded semiconductor solution provider serving automotive, industrial, infrastructure, and IoT industries. The company is seeking an early-career Cloud DevOps and AI Security Engineer to secure and scale AI infrastructure and development pipelines by supporting cloud security, automated deployments, monitoring, access management, and responsible AI-assisted engineering practices.

What you'll do:

• AI Infrastructure and Pipeline Security: As we move to adopt a more AI / Agentic workflow you will help secure emerging AI infrastructure and AI-enabled development by supporting security checks, documenting controls, validating tool configurations, and escalating potential risks under guidance from senior team members
• Security Monitoring: Review logs, alerts, system activity, and pipeline outputs to help identify, document, and escalate potential vulnerabilities or unusual behavior
• Cloud Infrastructure Support: Assist in provisioning, configuring, and maintaining core AWS services such as VPC, EC2, S3, IAM, Lambda, Docker, and Kubernetes
• Infrastructure as Code: Learn, update, and write basic Terraform, Serverless, or AWS CloudFormation templates under guidance from senior team members
• Access Management: Help manage user permissions and access controls using AWS IAM and least-privilege principles
• Team Collaboration: Work with developers, QA, and operations team members to troubleshoot issues, document findings, and support safe releases for customer-facing web platforms
• Deployment Support: Help maintain and improve automated CI/CD pipelines to support safe, reliable, and repeatable software delivery
• Documentation: Create and maintain clear technical documentation for architecture diagrams, deployment processes, access controls, and security protocols

What they're looking for:

• Cloud Fundamentals: Foundational understanding of AWS services, cloud computing concepts, networking basics, IAM, security groups, and common web infrastructure patterns
• Cloud Security Fundamentals: Basic familiarity with least privilege, access controls, encryption, secrets management, logging, and secure configuration practices
• Security Monitoring and Triage: Ability to review logs, alerts, system activity, and pipeline outputs, document findings clearly, and escalate potential risks
• Automation Exposure: Basic experience with scripting languages such as Python or Bash to automate repetitive operational or security-related tasks
• Version Control: Familiarity with Git workflows, Bitbucket pipelines, pull requests, branching strategies, and change tracking
• AI-Assisted Engineering: Awareness of how AI coding assistants and automation tools can be used responsibly, including protecting sensitive information, validating tool outputs, documenting AI-assisted changes, and following approved safe-use practices
• Degree in Computer Science, Cybersecurity, Software Engineering, Information Systems, or a related field, or equivalent practical experience
• Coursework, internships, graduate research, capstone projects, or hands-on work involving cloud security, DevSecOps, secure software development, application security, AI infrastructure, or responsible use of AI coding assistants are highly desirable
• Experience: 0–2 years of experience in IT support, systems administration, cloud operations, cybersecurity, software engineering, web operations, or a junior DevOps role
• Certifications: Relevant entry-level certifications, such as AWS Cloud Practitioner, CompTIA Security+, or equivalent, are helpful but not required