Cloud Infrastructure Engineer — AWS & AI Automation

Spotlio AS

Gerona

On-site

EUR 60,000 - 90,000

Full time

14 days+

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Job summary

Spotlio AS in Cataluña seeks an Infrastructure Engineer to design, maintain, and monitor scalable infrastructure enabling dev teams to deploy product updates efficiently. You’ll implement AI-assisted automations and collaborate across Support, QA, delivery, and analytics teams.

The role emphasizes building new development tools, automating release processes, and ensuring security while aligning with company values of Passion, Performance, Customer-centricity, and Innovation.

Qualifications

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

Responsibilities

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)