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Mid-Level
Cloud Security Engineer
Confirmed live in the last 24 hours
Applied Intuition
München, Bavaria, Germany
Remote
Posted January 14, 2026
Job Description
About Applied Intuition
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.
We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.
About the role
As the first Cloud Security Engineer in EMEA, you will play a foundational role in shaping and scaling the security posture of our platform across regions. Based in Munich, you will join our local Infrastructure team and collaborate closely with global counterparts to design and implement secure, reliable systems that power autonomy development.
In this role, you’ll take ownership of key security domains - including authentication, identity and access management, and cloud infrastructure hardening - and help define the technical standards that guide our security practices. You'll also build internal tools and frameworks that enable product and infrastructure teams to adopt security best practices by default. As a member of a globally distributed Security & Authentication team, you will work cross-functionally and directly with internal stakeholders and external customers to support evolving security requirements.
At Applied Intuition, you will:
- Design and implement security standards and tools across the Kubernetes fleet and major cloud providers (AWS, GCP, Azure) as well as on-prem and air-gapped environments
- Implement and monitor security measures to protect internal and external systems, networks, and data
- Build product features that help our customers manage access and usage of Applied Intuition products
- Develop and implement processes that are in compliance with legal and ethical standards and ensure that our customer data is protected and secured
- Take ownership over technical decisions, interact closely with users and customers to collect feedback, and contribute to a thoughtful, dynamic team culture
We're looking for someone who has:
- 5+ years of industry experience in software engineering, with a focus on designing and building secure, production-grade backend systems
- Bachelor’s degree or higher in Computer Science, Software Engineering, or a related technical discipline
- Proficient in one or more of the following programming languages: Go (Golang), Python or C++ with at least 3 years of backend development experience
- Deep expertise in Kubernetes security, including:
- Securing containerized workloads
- Implementing role-based access control (RBAC)
- Managing secrets securely using tools like cloud-native secret managers
- Experience deploying, operating, and securing systems on at least one major cloud provider (AWS, GCP, or Azure), including identity management, workload isolation, and audit logging
- Proven track record of independently driving secure system development from concept to production (zero-to-one)
pythongorustawsgcpazurekubernetesaibackenddata
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