About this role

We are looking for a Senior Infrastructure Engineer (f/m/x) to strengthen our cloud and platform foundations, empowering teams to build, deploy, and operate software solutions.

In this role, internally titled Infrastructure Engineer IV, you’ll work at the core of cloud infrastructure, developer experience, and reliability. You’ll design scalable and secure systems on AWS, evolve our Infrastructure-as-Code and CI/CD practices, and champion automation, observability, optimization, and continuous improvement.

Your first major area of ownership will be the infrastructure behind AI-powered capabilities at Eye Security: building the secure, observable, and cost-controlled environment that takes agents and LLM-backed services from prototype to production. This is your starting point, not the permanent boundary of the role — over time, you’ll work across our wider cloud platform, developer experience, reliability, and infrastructure strategy.

This is a platform and infrastructure engineering role, not an ML research or applied science position. You will not train or fine-tune models, build feature pipelines, or work as a prompt engineer. We also don’t expect you to have worked with every AWS AI service listed below — strong platform fundamentals and real experience bringing AI-powered systems into production matter more than familiarity with specific services.

What you will do

• Design, build, and maintain highly scalable, resilient, and secure infrastructure on AWS.
• Lead our Infrastructure-as-Code practices using Terraform, including reusable modules and deployment patterns.
• Build the deployment patterns, workload identity, access controls, and operational guardrails required to run agents and LLM-backed services in production, covering tool access, secrets, data handling, service quotas, and cost.
• Evolve our monitoring and observability strategy using tools such as Grafana and Sentry, including distributed tracing across agent and tool calls, usage and cost attribution, and failures that are semantic rather than operational.
• Establish practical ways to evaluate non-deterministic behaviour and catch regressions before and after deployment.
• Continuously improve automation, deployment pipelines, system reliability, performance, and technical debt.
• Mentor mid-level engineers and share knowledge through documentation, reviews, and technical discussions.
• Communicate clearly about technical trade-offs, timelines, and priorities, ensuring alignment with product and engineering goals.
• Balance multiple priorities and adapt effectively in a fast-changing scale-up environment.

What you need

• 6+ years of hands-on experience in Platform Engineering, DevOps, SRE, or related fields, with significant experience in AWS.
• Strong expertise in AWS, Infrastructure-as-Code with Terraform, GitOps, CI/CD systems, and observability.
• Experience authoring reusable Terraform modules for other teams, including versioning and release practices — not only working within an existing codebase.
• Ability to write and maintain production code in a language such as Go, Python, or TypeScript.
• 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, with evidence that it was genuinely useful.
• You can speak concretely about the decisions you made around tool use, context and state, evaluation, failure handling, autonomy, cost, and latency, as well as how you deployed and operated the system and what it changed for the people using it.
• Strong understanding of security best practices, including least-privilege design for workloads that hold credentials or act on behalf of users, as well as secure coding and development principles.
• Proven ability to take initiative, solve complex problems, and deliver in ambiguous environments.
• Skilled at breaking down complex problems into practical solutions, prioritizing impact and maintainability over perfectionism.
• An analytical mindset with strong technical and product awareness.
• Experience working in a start-up or scale-up environment and adapting to fast-changing needs.
• Excellent communication and collaboration skills, with the ability to influence technical and non-technical stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
• Fluency in English is a must.

Nice to have

• Experience with Amazon Bedrock, Bedrock AgentCore, Bedrock Flows, Knowledge Bases, or Guardrails.
• Experience deploying agent frameworks such as Strands Agents, LangGraph, or similar, and familiarity with Model Context Protocol or tool gateways.
• Experience with automated evaluation of model or agent behaviour, prompt and configuration versioning, and regression testing for non-deterministic systems.
• Experience instrumenting distributed systems with OpenTelemetry.
• Experience running AI or data workloads under European data-residency constraints.
• Background in cost optimization, compliance, or developer platform enablement.
• Experience with additional observability or security tools beyond Grafana and Sentry.

What we offer

• A meaningful mission: protect organizations across Europe from real-world cyber threats.
• Work with top-tier professionals from national CERTs, intelligence agencies, and leading tech backgrounds.
• A remote-friendly culture with quarterly meetups and annual company retreats in locations across Europe.
• Thursday socials to stay connected.
• A generous time-off policy, including wellbeing and volunteering days.

About this role

We are looking for a Senior Infrastructure Engineer (f/m/x) to strengthen our cloud and platform foundations, empowering teams to build, deploy, and operate software solutions.

In this role, internally titled Infrastructure Engineer IV, you’ll work at the core of cloud infrastructure, developer experience, and reliability. You’ll design scalable and secure systems on AWS, evolve our Infrastructure-as-Code and CI/CD practices, and champion automation, observability, optimization, and continuous improvement.

Your first major area of ownership will be the infrastructure behind AI-powered capabilities at Eye Security: building the secure, observable, and cost-controlled environment that takes agents and LLM-backed services from prototype to production. This is your starting point, not the permanent boundary of the role — over time, you’ll work across our wider cloud platform, developer experience, reliability, and infrastructure strategy.

This is a platform and infrastructure engineering role, not an ML research or applied science position. You will not train or fine-tune models, build feature pipelines, or work as a prompt engineer. We also don’t expect you to have worked with every AWS AI service listed below — strong platform fundamentals and real experience bringing AI-powered systems into production matter more than familiarity with specific services.

What you will do

• Design, build, and maintain highly scalable, resilient, and secure infrastructure on AWS.
• Lead our Infrastructure-as-Code practices using Terraform, including reusable modules and deployment patterns.
• Build the deployment patterns, workload identity, access controls, and operational guardrails required to run agents and LLM-backed services in production, covering tool access, secrets, data handling, service quotas, and cost.
• Evolve our monitoring and observability strategy using tools such as Grafana and Sentry, including distributed tracing across agent and tool calls, usage and cost attribution, and failures that are semantic rather than operational.
• Establish practical ways to evaluate non-deterministic behaviour and catch regressions before and after deployment.
• Continuously improve automation, deployment pipelines, system reliability, performance, and technical debt.
• Mentor mid-level engineers and share knowledge through documentation, reviews, and technical discussions.
• Communicate clearly about technical trade-offs, timelines, and priorities, ensuring alignment with product and engineering goals.
• Balance multiple priorities and adapt effectively in a fast-changing scale-up environment.

What you need

• 6+ years of hands-on experience in Platform Engineering, DevOps, SRE, or related fields, with significant experience in AWS.
• Strong expertise in AWS, Infrastructure-as-Code with Terraform, GitOps, CI/CD systems, and observability.
• Experience authoring reusable Terraform modules for other teams, including versioning and release practices — not only working within an existing codebase.
• Ability to write and maintain production code in a language such as Go, Python, or TypeScript.
• 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, with evidence that it was genuinely useful.
• You can speak concretely about the decisions you made around tool use, context and state, evaluation, failure handling, autonomy, cost, and latency, as well as how you deployed and operated the system and what it changed for the people using it.
• Strong understanding of security best practices, including least-privilege design for workloads that hold credentials or act on behalf of users, as well as secure coding and development principles.
• Proven ability to take initiative, solve complex problems, and deliver in ambiguous environments.
• Skilled at breaking down complex problems into practical solutions, prioritizing impact and maintainability over perfectionism.
• An analytical mindset with strong technical and product awareness.
• Experience working in a start-up or scale-up environment and adapting to fast-changing needs.
• Excellent communication and collaboration skills, with the ability to influence technical and non-technical stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
• Fluency in English is a must.

Nice to have

• Experience with Amazon Bedrock, Bedrock AgentCore, Bedrock Flows, Knowledge Bases, or Guardrails.
• Experience deploying agent frameworks such as Strands Agents, LangGraph, or similar, and familiarity with Model Context Protocol or tool gateways.
• Experience with automated evaluation of model or agent behaviour, prompt and configuration versioning, and regression testing for non-deterministic systems.
• Experience instrumenting distributed systems with OpenTelemetry.
• Experience running AI or data workloads under European data-residency constraints.
• Background in cost optimization, compliance, or developer platform enablement.
• Experience with additional observability or security tools beyond Grafana and Sentry.

What we offer

• A meaningful mission: protect organizations across Europe from real-world cyber threats.
• Work with top-tier professionals from national CERTs, intelligence agencies, and leading tech backgrounds.
• A remote-friendly culture with quarterly meetups and annual company retreats in locations across Europe.
• Thursday socials to stay connected.
• A generous time-off policy, including wellbeing and volunteering days.