Security Engineer

CAST AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, CAST AI continuously optimises performance, reliability and efficiency in production.

More than 2,100 companies rely on CAST AI, including Akamai, BMW, Cisco, FICO, Hugging Face, NielsenIQ, Swisscom and TGS. We are headquartered in Miami and operate as a remote-first company across 34 countries in Europe, North America, Latin America and APAC. In January 2026, CAST AI reached unicorn status following a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group.

CAST AI is hiring its first dedicated Security Engineer.

Security is currently handled alongside other responsibilities by engineers across the product organisation. As the company grows, we need someone whose full-time focus is understanding the security of our platform, identifying the highest-impact risks and helping engineering teams address them.

CAST AI operates inside customers’ production environments. Customers grant the platform cloud credentials, cluster access and permission to delete, move and resize workloads. Every permission needs to be justified, every action needs to be attributable and every component needs to be assessed as part of a wider attack surface.

You will work across a multi-tenant platform spanning AWS, GCP and Azure, Kubernetes environments, microservices, CI/CD pipelines and AI agents that make autonomous decisions in production. You will help make the secure path the easiest path for engineering teams.

This is a technical, hands-on individual contributor role. You will not be expected to implement every security control yourself, but you will identify risks, define practical mitigations, guide the teams responsible for implementation and drive the most important issues through to closure.

You will report to Mantas Norvaiša and work closely with engineering teams, the Platform team and Danielius, who leads the non-technical side of compliance.

• Learn CAST AI’s architecture, infrastructure and engineering workflows, then identify security flaws and material risks.
• Set up, operate and continuously tune cloud security tooling such as Wiz so it produces high-signal findings that engineering teams can act on.
• Build threat models for the product and backend architecture, including trust boundaries, service-to-service authentication, customer-cluster access, secrets and attack paths.
• Assess and prioritise findings using evidence, business impact and exploitability rather than treating every alert equally.
• Present the most important risks to engineering and company leadership and build the case for addressing them.
• Advise engineering teams on practical security improvements.
• Drive the implementation of security controls across engineering, including production access, identity, secrets management and secure CI/CD practices.
• Work with the relevant teams to ensure security controls are implemented, tracked and maintained.
• Help translate compliance requirements into meaningful technical work and evidence.
• Contribute to security standards for cloud infrastructure, Kubernetes, software supply chains and AI-enabled systems.
• Support the development of security signals and incident-response practices while helping reduce alert noise.
• Use scripting, prototypes or code where helpful to validate risks, automate security workflows or support engineering teams. This is not a software development role, but strong software-engineering fundamentals are important.

• At least 5–6 years of professional security experience. Around 10 years or more would be ideal.
• Hands-on experience setting up and running cloud security tooling in production, such as Wiz, Upwind or a similar platform, and turning findings into fixes.
• Strong understanding of cloud infrastructure security across compute, networking, IAM, storage and service communication.
• Practical experience with at least one of AWS, GCP or Azure, with the ability to reason about how cloud systems work and how they can fail.
• Strong understanding of Kubernetes and cloud-native infrastructure.
• Experience threat modelling real systems using STRIDE or a similar method, and the ability to lead engineering teams through the process.
• Strong software-engineering fundamentals, including the ability to understand and reason about software architecture, distributed systems and infrastructure.
• Ability to write or review code and automation in Go or Python.
• Strong written and spoken English.
• A proactive, adaptable approach and comfort working in a fast-moving environment where the security function is being built from the ground up.

• Deep hands-on experience with AWS, GCP or Azure, including compute, networking and storage internals.
• Kubernetes security experience covering RBAC, admission control, network policies and Pod Security Standards.
• Experience hardening real production Kubernetes clusters.
• Identity and secrets-management experience, including least-privilege IAM, workload identity and secrets rotation.
• Detection engineering or incident-response experience, including tuning security signals and reducing false positives.
• Experience with SOC 2, ISO 27001, FedRAMP or similar compliance frameworks.
• Software supply-chain security experience, including SBOMs, dependency scanning, container-image scanning, signing and CI/CD security.
• Experience securing AI and agent-based systems, including prompt injection, excessive agency and tool abuse risks.
• Familiarity with AI coding agents and agentic development workflows.
• Experience with Terraform and infrastructure-as-code security.
• Security certification such as OSCP, CISSP or a comparable qualification. We value what you have built and fixed more than certifications alone.

• Security: Wiz
• Cloud and orchestration: Kubernetes, GCP, AWS, Azure
• Infrastructure as code: Terraform
• Programming: Go, Python
• Databases and storage: PostgreSQL, ClickHouse, Google Cloud Storage
• Messaging and APIs: GCP Pub/Sub, gRPC, REST
• Observability: Grafana, VictoriaMetrics, VictoriaLogs, VictoriaTraces
• CI/CD and GitOps: GitLab CI, Argo CD, Kargo

You do not need experience with every technology listed. We are looking for deep security judgement, strong infrastructure fundamentals and the ability to learn the rest quickly.

• A chance to build the first dedicated security function at a fast-growing cloud infrastructure company.
• Direct influence over how security is designed, prioritised and implemented across the organisation.
• Exposure to large-scale multi-cloud, Kubernetes and AI infrastructure.
• Close collaboration with engineering and platform teams rather than security work in isolation.
• A flexible, remote-first working environment across Europe.
• Equity options.
• Learning and development budget, including access to relevant courses and conferences.
• Equipment budget and team-building support.
• Additional time off and company events.

1. Introductory conversation with Mantas Norvaiša.
2. Security-focused threat modelling exercise. You will be given a system to analyse and model. This is similar to a system-design interview, but focused on trust boundaries, threats, attack paths and mitigations.
3. Conversation with Danielius about compliance and cross-functional working.
4. Culture check interview