Senior System Engineer

Senior System Engineer (DevOps)

The job in short

Backbase just launched its new AI-powered Banking Platform globally. We are helping banks go from just experimenting with AI to actually using it to get things done. This platform automates key tasks and boosts productivity for both customer-facing and back-office teams, turning the potential of AI into real business results

We operate with a bold startup mindset prioritizing speed, autonomy, and breakthrough innovation.

As a System Engineer(DevOps) you'll work in a team responsible for design, development and maintenance of the platform.

At each level of the architecture we apply industry standards ensuring stability, security and scalability while remaining cost efficient.

You should have experience in building and running platforms or infrastructures in production.

Considering the area of AI surrounding tools and frameworks are rapidly evolving, we are looking for engineers with a curious mindset and doer mentality.

If you have passion in technology, eager to learn, adopt, deliver and work in short fast phased iterations - please go ahead and apply.

How about you

The ideal candidate will have a strong background in building and maintaining infrastructure using public cloud ( Azure, AWS, GCP), automation (python/golang), observability (prometheus/grafana), infrastructure as code (IaC), identity and access management (IAM), security and DevOps practices.

This role requires familiarity with concepts of AI infrastructure and solutions offered by major players, emerging patterns of building GenAI products.

Preferred Qualifications:

Experience working with AI infrastructure is a big plus.

It's not mandatory but let's have a chat if you already have experience in of the following areas:

• Experience with cloud based AI solutions: Azure Cloud Foundry/Amazon Bedrock
• Observability and Security in AI ( Langfuse)
• LLM Gateways ( LiteLLM)
• Vector Databases
• Big bonus is experience with designing, deploying, maintaining MCP, RAG, Agents

Required Qualifications:

Besides new and shiny AI/ LLM we believe that a strong proven background in engineering is essential. So if you yet don't have experience with AI but have a good background in areas highlighted below. Please, do not hesitate and apply:

• At least 5 years in a similar role running production workloads on public cloud ( Azure - preferred, AWS, GCP)
• Linux based OS, containerisation ( Docker, Containerd) - configuration, optimisation, monitoring, troubleshooting
• Kubernetes ( Azure Kubernetes Service, Google Kubernetes Engine) - expert level
• Observability - Prometheus, Grafana, Opentelemtry, concept of metrics
• Infrastructure as a Code, config management, GitOps - Terraform, Helm, ArgoCD
• Strong troubleshooting skills, experience with on-call
• Automation and programming/scripting - python, golang
• Deep understanding of infrastructure security
• You have strong communication skills