Infrastructure Engineer

Role Overview

• Carry out the tasks assigned by the Systems Manager (V2)
• Build and set up new development tools and infrastructure (V1,V2,V4)
• Understand the needs of stakeholders and convey them to developers (V1, V2, V3, V4)
• Work on ways to automate and improve development and release processes (V1, V2, V4)
• Ensure that systems are safe and secure against cybersecurity threats (V1, V2, V3, V4)
• Participate in compliance and certification initiatives (V1, V2, V4)
• Identify technical problems and develop software updates and ‘fixes’ (V1, V2, V3, V4)
• Monitor the status of systems in operation, detect failures, bottlenecks or other incidents (V1, V2, V4)
• Work with software developers and software engineers to ensure that development follows established processes and works as intended (V1, V2, V3, V4)
• Plan out projects and be involved in project management decisions (V1, V2, V3, V4)
• Participate in the daily stand-up meetings, retrospectives and other meetings involved in the SCRUM process (V1, V2, V3, V4)
• Collaborate with the Support, QA, delivery, partner services and analytics teams (V1, V2, V3, V4)
• Track and log the time spent in the different tasks assigned (V2)
• Use AI coding assistants and agentic tools (e.g. Claude / Claude Code, Copilot, Cursor) to accelerate authoring and review of IaC, deployment scripts, and automation — applying human judgment to validate output before it reaches production (V1, V2, V4)
• Apply AI to operational signals — log, metric, and trace analysis, incident triage, and root-cause investigation — to detect failures and bottlenecks faster (V2, V3, V4)
• Build and maintain AI-assisted automations in pipelines, runbooks, and internal tooling (e.g. LLM-driven checks, summarization of alerts, automated documentation) (V1, V2, V4)
• Use AI tools responsibly and securely: never expose secrets, credentials, or customer data in prompts, and follow established data-handling and compliance practices when working with AI services (V2, V3, V4)
• Contribute to team-wide AI adoption by sharing effective prompts, workflows, and patterns, and helping raise the team's overall AI fluency (V1, V4)

Requirements

• Have availability to work, if needed, in our US team/customer’s time zone, within the range 14:00 to 19:00 CET/CEST
• Basic DBA proficiency
• Experienced in managing and scaling Amazon Web Services (AWS):
• RDS
• Cloud Watch
• Cloudformation, Terraform, Serverless or any other IaC systems
• EC2
• ELB and WAF
• Redshift
• CloudFront
• S3
• Route53
• ECS and deployment of Docker containers
• Lambda
• Redis
• etc.
• Proficient with git and git workflows
• Experienced in using server monitoring tools
• Infrastructure as Code: Terraform, CloudFormation, etc
• Experience with CD-CI Tools: CircleCI, Bitbucket Pipelines, etc..
• Serverless Framework
• Hands-on experience with at least one AI coding assistant or agentic developer tool (Claude Code, GitHub Copilot, Cursor, or similar) in a real engineering workflow
• Ability to prompt effectively for technical tasks — decomposing problems, providing context, and iterating — to get reliable results from AI tools
• Sound judgment about AI limitations: reviews, tests, and verifies AI-generated code and configuration rather than accepting it blindly; recognises when AI is and isn't the right tool
• Awareness of the security and privacy considerations of using AI services (data leakage, prompt injection, supply-chain risk)
• Desirable: experience building automations on top of LLM APIs, or with agent/MCP-style tooling and AI-powered observability (AIOps)
• Having a problem-solving attitude.
• Motivated to work in a development team and collaborate with other team members: support, delivery, and resort partner services
• Proficient in writing and having a conversation in English

Tech Stack

• Amazon Redshift
• AWS
• Cloud
• Cyber Security
• Docker
• EC2
• Redis
• Terraform

Benefits

• Minimum 100% availability as an employee of Spotlio EMEA SL. Willingness to work outside office hours with notice.