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.

Catalate

Open Positions (1)

Engineering

Infrastructure Engineer