DevOps Engineer

Posted 2 Days Ago
Be an Early Applicant
Turin, ITA
Hybrid
50K-60K Annually
Mid level
Artificial Intelligence • Machine Learning • Software • Analytics
The Role
Design, build, and maintain scalable cloud infrastructure for a SaaS application. Administer highly available Kubernetes clusters, implement Infrastructure as Code with Terraform or CloudFormation, and monitor and troubleshoot system performance. The role also involves automation using Python, Go, or Bash; applying networking and security best practices; supporting microservices architecture; and collaborating with cross-functional teams and customers.
Summary Generated by Built In

Title: Infrastructure/DevOps/Cloud Engineer

Location: Turin, Italy (hybrid)

Reporting to: CTO

Before you apply: Nebuly is where the bar is high and the vision is bold—we move fast, think deeply, and push each other to build the future of AI products. If you’re ready to give your best, we’d love to hear from you.

About Nebuly

Nebuly is a fast-growing, VC-backed startup building the platform that proves the ROI of enterprise AI.
Every enterprise function — sales, customer support, HR, finance — is deploying AI agents at scale, and budgets are following fast. But most companies can't answer a basic question: is this spend actually working? Every enterprise deploying AI agents is asking the same question: is this actually delivering value? Today, almost none of them can answer it. The signal that could answer it is right there — millions of conversations happening every day between employees, customers, and these agents — but it's unstructured, high-volume, and invisible without the right infrastructure. So the ROI question stays unanswered, not because the answer doesn't exist, but because no one can see it. Nebuly makes that signal visible. It sits on top of any enterprise AI deployment, turns those conversations into a clear answer — is this working, and where — and connects the dots back to ROI. Think of it as the accountability layer for enterprise AI: connect once, see the impact, prove the value — with no data ever leaving your environment.
Every new data category has created a new software category. CRM turned customer interactions into pipeline accountability. Product analytics turned user behavior into growth accountability. Nebuly is building that same layer for AI — turning millions of invisible conversations into a clear answer on value.
Our customers include Oura, CNH Industrial, Vodafone, and Moncler. Demand is accelerating fast, and we're building the team to match.


Examples of your daily responsibilities

As an Infrastructure/DevOps/Cloud Engineer at Nebuly, you will play a pivotal role in designing, building, and maintaining our robust and scalable cloud infrastructure. Join our dynamic team of experts who are passionate about leveraging cloud computing, Kubernetes (K8s), DevOps practices, and Infrastructure as Code (IaaC) to ensure a highly available and efficient environment for our SaaS web-based application. Your expertise will contribute to delivering reliable and scalable solutions while driving automation and efficiency across our infrastructure. Your responsibilities will include:

  • Design, implement, and manage our cloud infrastructure using leading cloud providers such as AWS, Azure, or Google Cloud Platform.

  • Develop and maintain Kubernetes (K8s) clusters, ensuring high availability, scalability, and efficient resource utilization.

  • Drive Infrastructure as Code (IaaC) initiatives, leveraging tools such as Terraform for provisioning and managing cloud resources.

  • Monitor and troubleshoot infrastructure performance, ensuring the reliability and availability of our systems.

What we look for
  • Minimum of 3 years of professional experience in infrastructure engineering, DevOps, or cloud engineering roles.

  • Strong knowledge and hands-on experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.

  • Expertise in Kubernetes cluster administration.

  • Experience with Infrastructure as Code (IaaC) tools like Terraform or CloudFormation.

  • Strong understanding of networking concepts, security best practices, and monitoring tools.

  • Familiarity with logging and monitoring tools such as ELK Stack, Prometheus, or Grafana.

  • Familiarity with scripting languages (e.g., Bash, Python) for automation and tooling.

  • Ability to work collaboratively in cross-functional teams and communicate effectively.

  • Ability to work in contact with customers teams

  • Professional experience in Python or Go

  • Strong knowledge and experience with microservices architecture and building scalable systems.

What we offer

High-impact work in small, fast-moving teams. At Nebuly, you’ll work in small, entrepreneurial teams with a high degree of ownership and autonomy. Regardless of your seniority, your contributions will have a direct impact—from the earliest ideas to product launch. You’ll have the chance to build things from scratch and see your code evolve into real products used at scale.

A platform for real growth. As more and more companies rely on our platform to understand and optimize their AI experiences, new challenges and opportunities emerge constantly. This means your role won’t stay static—you’ll keep growing with the product, facing new technical and strategic problems as we scale.

Competitive pay + equity. We offer a salary in the range of €50,000–60,000 gross per year, depending on the outcome of the technical interview, plus meaningful stock options in a fast-scaling company.

The selection process

For most roles at Nebuly, here’s what our hiring process typically looks like:

  1. Introductory Call (30min): You’ll first speak with the person who initially contacted you or the hiring coordinator for the role. This is an informal chat where we’d love to learn more about you—what brought you to apply, your interests, and what excites you. We were impressed by your profile and want to give you space to ask questions and get a better sense of what we do at Nebuly. The whole conversation is held in English.

  2. Logic Challenge (30min): A test with logic-based questions. This helps us understand how you approach unfamiliar problems.

  3. Technical Session (1hr): This is a round of technical questions, typically with another member of the team or the lead of your function. It’s a chance for us to go deeper into your technical thinking and problem-solving approach, and for you to show how you tackle realistic challenges you’d face at Nebuly.

  4. Role-Focused Project (2 hrs): At this stage, we’re genuinely excited about the possibility of working together. We’ll propose a short project that reflects the kind of work you’d actually be doing at Nebuly. You’ll have full flexibility on timing—we’ll work around your schedule to make sure it’s manageable and enjoyable.

  5. Offer : If it’s a match, we’ll give you a call to walk through the offer details—compensation, starting date, next steps—and answer any questions you might have.

Skills Required

  • Minimum of 3 years of professional experience in infrastructure engineering, DevOps, or cloud engineering roles.
  • Strong knowledge and hands-on experience with AWS, Azure, or Google Cloud Platform.
  • Expertise in Kubernetes cluster administration.
  • Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
  • Strong understanding of networking concepts, security best practices, and monitoring tools.
  • Familiarity with ELK Stack, Prometheus, or Grafana.
  • Familiarity with Bash or Python for automation and tooling.
  • Ability to work collaboratively in cross-functional teams and communicate effectively.
  • Ability to work with customer teams.
  • Professional experience in Python or Go.
  • Strong knowledge and experience with microservices architecture and building scalable systems.
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The Company
23 Employees
Year Founded: 2022

What We Do

Nebuly provides an enterprise user-analytics platform for AI agents. It analyzes conversations between employees or customers and deployed AI assistants, helping organizations understand what users ask, how agents respond, whether users achieve their goals, and where adoption, unmet needs, satisfaction, and return-on-investment signals emerge. The platform connects to existing chatbots and supports enterprise-scale, secure, on-premises, or private-cloud deployments within customer infrastructure.

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