Cloud Infrastructure Engineer

Job Overview

In GoodData.AI, we are expanding our team dedicated to the cloud operation of our unique analytical platform, designed for creating analytical data products for our customers. We are seeking an experienced operations engineer to join our Cloud Infrastructure team. The successful candidate should be an enthusiastic professional who is deeply interested in cutting-edge technologies and is able to learn new things quickly.

How we work with AI

GoodData.AI is an AI-first company. AI agents and assistants are part of how we design, build, and operate the platform every single day, and we are looking for people who want to work this way too.

Your role

We're looking for a technically strong, experienced engineer or cloud architect to be responsible for cloud deployments across virtual machines, Kubernetes clusters and physical servers. You'll work closely with engineering, architects, security, and product teams to ensure that our platforms are reliable, scalable, and secure.

What you'll do

• Design and maintain tooling and infrastructure for deployment, scaling and monitoring of our platform.
• Design and manage cloud-based (AWS, Azure, GCP) and on-premise infrastructure (VMs, OpenStack, K8s clusters, bare metal).
• Use AI agents daily, from writing and reviewing infrastructure code to automating operational and reporting tasks.
• Participate in planning, execution and review of platform improvements and new deployments.
• Drive technical decisions and improvements in areas such as automation, availability and observability.
• Ensure smooth integration with logging, alerting and security systems.
• Be responsible for meeting SLA and availability targets.
• Support knowledge sharing and growth within the team.
• Participate in 24/7 on-call rotation (approx. 1 week a month).

What you should bring

• 4+ years of hands-on experience in infrastructure / operations / SRE roles.
• Strong Linux administration and troubleshooting skills.
• Experience with deployment and management of:
• Services in AWS, Azure or Google Cloud
• VMs (e.g. KVM, VMware, OpenStack),
• Kubernetes clusters (on-prem or cloud),
• Bare-metal servers.
• Proficiency in shell scripting and at least one scripting language (e.g. Python).
• Working knowledge of networking, TCP/IP, and common protocols.
• Understanding of configuration management and infrastructure-as-code principles.
• Genuine interest in AI-assisted engineering: you treat AI agents as part of your toolchain and you are willing to build your daily workflow around them.
• Good communication skills in English, both written and spoken.

Nice to have

• Experience with tools like: Docker, Ansible, Puppet, Terraform, Git. Familiarity with cloud platforms (AWS, GCP, Azure or private clouds).
• Hands-on experience with agentic AI tooling (Claude Code, Codex, Copilot, Cursor or similar) beyond autocomplete: agent workflows, custom skills, MCP integrations.
• Experience in security-conscious environments.
• Background in agile environments and cross-functional teams.

Why join us

You'll have the opportunity to be part of a highly skilled team in a key infrastructure role. Work on hybrid deployments: cloud, on-premise and hardware.

Work AI-first with senior engineers who adopted agentic tooling early and use it seriously, so you will learn practices here that most companies are only starting to explore.

Influence platform strategy and drive automation and reliability forward.

Be part of a supportive, pragmatic engineering culture.

About GoodData.AI

At GoodData.AI, we’re building the future of agentic AI for data intelligence.

Our full-stack data intelligence platform empowers companies to turn raw data into real business impact — from agentic AI apps to embedded analytics that scale securely and seamlessly. With GoodData.AI, organizations don’t just analyze data, they monetize it.

But what really sets GoodData.AI apart is our mission: to put intelligence wherever decisions are made. That’s why we’ve built a platform that’s AI-native, composable, and built for the way modern enterprises work.