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Eye Security is a European cybersecurity company combining cutting-edge technology with embedded cyber insurance solutions. With over 200 FTEs and international operations, the company brings together talent from intelligence, military, tech, and consulting backgrounds to make enterprise-grade cybersecurity accessible to all businesses.
You will join as a Senior Infrastructure Engineer (internally titled Infrastructure Engineer IV) to strengthen cloud and platform foundations. Your primary focus will be building secure, observable, and cost-controlled infrastructure for AI-powered capabilities—specifically the infrastructure behind agents and LLM-backed services at Eye Security, taking them from prototype to production. Over time, you'll expand across the wider cloud platform, developer experience, reliability, and infrastructure strategy.
This is a platform and infrastructure engineering role, not ML research or applied science. You will not train or fine-tune models, build feature pipelines, or work as a prompt engineer.
Key responsibilities:
- Design, build, and maintain highly scalable, resilient, and secure infrastructure on AWS
- Lead Infrastructure-as-Code practices using Terraform, including reusable modules and deployment patterns
- Build deployment patterns, workload identity, access controls, and operational guardrails for agents and LLM-backed services in production
- Evolve monitoring and observability strategy using Grafana and Sentry, including distributed tracing and cost attribution
- Establish practical ways to evaluate non-deterministic behavior and catch regressions
- Continuously improve automation, deployment pipelines, system reliability, and technical debt
- Mentor mid-level engineers and share knowledge through documentation and technical discussions
- Communicate clearly about technical trade-offs, timelines, and priorities
- Balance multiple priorities in a fast-changing scale-up environment
Requirements:
- 6+ years of hands-on experience in Platform Engineering, DevOps, SRE, or related fields, with significant AWS experience
- 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
- Ability to write and maintain production code in Go, Python, or TypeScript
- Hands-on experience building and shipping a non-trivial agent or LLM-backed workflow in production or as a side project with real users
- Concrete understanding of decisions around tool use, context and state, evaluation, failure handling, autonomy, cost, and latency
- Strong understanding of security best practices, including least-privilege design for workloads with credentials
- Proven ability to take initiative, solve complex problems, and deliver in ambiguous environments
- Ability to break down complex problems into practical solutions, prioritizing impact and maintainability
- Analytical mindset with strong technical and product awareness
- Experience in start-up or scale-up environments
- Excellent communication and collaboration skills
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- Fluency in English
Nice to have:
- Experience with Amazon Bedrock, Bedrock AgentCore, Bedrock Flows, Knowledge Bases, or Guardrails
- Experience deploying agent frameworks such as Strands Agents or LangGraph
- Experience with automated evaluation of model or agent behavior and regression testing for non-deterministic systems
- Experience instrumenting distributed systems with OpenTelemetry
- Experience running AI workloads under European data-residency constraints
- Background in cost optimization, compliance, or developer platform enablement
- Experience with additional observability or security tools
