Senior Infrastructure Engineer – AI Platform (f/m/x)
About this role
The day-to-day work for the Senior Infrastructure Engineer on the AI Platform involves strengthening the cloud and platform foundations at Eye Security. This role is central to empowering development teams by ensuring they have scalable, secure, and reliable environments to build, deploy, and operate software solutions. A primary focus will be on building the infrastructure that supports AI-powered capabilities, specifically creating the secure, observable, and cost-controlled environment needed to move agents and LLM-backed services from initial prototype to production. Over time, the engineer will expand their scope to encompass the wider cloud platform, developer experience, reliability, and overall infrastructure strategy for the company.
This position is fundamentally a platform and infrastructure engineering role, not an ML research or applied science position. The focus is on the engineering discipline required to productionize AI systems, emphasizing robust infrastructure design, automation, and operational excellence. The engineer will be responsible for defining the guardrails, access controls, and operational mechanisms necessary for these advanced services to run reliably and cost-effectively in a production setting.
Candidates who thrive in fast-changing scale-up environments and possess a strong analytical mindset coupled with technical and product awareness would be well-suited for this role. Success in this position requires the ability to balance multiple priorities, clearly communicate technical trade-offs, and take initiative to solve complex problems.
What you will do
- Design, build, and maintain highly scalable, resilient, and secure infrastructure on AWS.
- Lead Infrastructure-as-Code practices using Terraform, including the creation of reusable modules and deployment patterns.
- Build the necessary deployment patterns, workload identity, access controls, and operational guardrails for running agents and LLM-backed services in production.
- Evolve the monitoring and observability strategy by implementing tools like Grafana and Sentry, including distributed tracing and cost attribution.
- Establish methods to evaluate non-deterministic behavior and detect regressions before and after deployments.
- Continuously improve automation, deployment pipelines, system reliability, and technical debt.
- Mentor mid-level engineers and share knowledge through documentation and technical discussions.
- Communicate clearly regarding technical trade-offs, timelines, and priorities to align with engineering goals.
What you need
- Possess six or more years of hands-on experience in Platform Engineering, DevOps, SRE, or related fields, with substantial experience in AWS.
- Demonstrate strong expertise in AWS, Infrastructure-as-Code using Terraform, GitOps, CI/CD systems, and observability tools.
- Must have experience authoring reusable Terraform modules for other teams, including managing versioning and release practices.
- Ability to write and maintain production code in a language such as Go, Python, or TypeScript.
- Require hands-on experience building and shipping a non-trivial agent or LLM-backed workflow, either in production or as a side project with real users.
- Must be able to articulate decisions made regarding tool use, context, state, evaluation, failure handling, autonomy, cost, and latency.
- Possess a strong understanding of security best practices, particularly least-privilege design for sensitive workloads.
- Proven ability to take initiative, solve complex problems in ambiguous settings, and prioritize impact and maintainability.
Nice to have
- Experience with specific AWS AI services
Benefits
- Hybrid work location
Skills and tech stack
Questions candidates ask
What is the remote policy?
The location listed for this role is The Hague, with a hybrid work arrangement. The posting does not specify the details of the remote policy.
What is the compensation structure?
The posting does not provide any details regarding the salary or compensation structure for this role.
What is the primary technology stack?
The core technologies mentioned include AWS, Infrastructure-as-Code with Terraform, GitOps, CI/CD systems, and observability tools like Grafana and Sentry.
What is the team structure like?
The role involves mentoring mid-level engineers and sharing knowledge through documentation and technical discussions, indicating a collaborative team environment.