(Senior) DevOps Engineer (m/f/d)

Blockbrain•Stuttgart, AR

30d•Hybrid

About The Position

Blockbrain is hiring a Senior DevOps Engineer to join its Platform team and own the reliability of the systems its AI agents run on. This is a reliability engineering role focused on treating operations as a software problem: defining and measuring platform health, maintaining production reliability, automating manual procedures, and addressing root causes when failures occur. The position covers SLOs and SLIs, error budgets, on-call operations, incident command, blameless post-incident reviews, production readiness, capacity planning, Kubernetes and cloud infrastructure, observability, automation, cost visibility, and platform security. The engineer will also use coding agents and other AI capabilities in day-to-day infrastructure and reliability work, automate operational workflows with AI in the loop, and provide operator feedback on Blockbrain’s tools. This is a full-time role based on-site in Stuttgart, Hamburg, or Munich three days per week, with flexible working hours. Blockbrain is an AI startup building a compliant, scalable knowledge management platform for mid-sized and enterprise companies in the DACH region.

Requirements

At least 5 years of experience in DevOps, SRE, or platform engineering.
Hands-on experience running Kubernetes in production.
Experience ideally includes operating production SaaS at scale.
Clear communication and the ability to remain calm under pressure, coordinate incidents, and write useful post-mortems.
Ability to work in English.
Experience or skills with Kubernetes, Terraform or infrastructure as code, CI/CD, observability, a major cloud platform, scripting, secrets management, and policy as code.
Strong ownership, a blameless mindset, an inclination toward automation, calm incident response, and a security-by-default mindset.
A degree in computer science or a related field, or equivalent hands-on experience.

Nice To Haves

German language skills.
Experience operating production SaaS at scale.
Experience with GitHub Actions, Prometheus, Grafana, distributed tracing, AWS, Azure, GCP, Python, Go, or TypeScript.
Openness to using AI as a daily co-pilot; prior AI expertise is not required.

Responsibilities

Define and own platform SLOs and SLIs, and manage error budgets against them.
Participate in on-call, act as incident commander, and run blameless post-incident reviews with meaningful follow-up actions.
Conduct production readiness work and capacity planning ahead of demand.
Run and harden the Kubernetes platform, including Helm, GitOps, and service mesh, and manage the underlying cloud infrastructure using Terraform and multi-region approaches.
Own observability across metrics, logs, and distributed tracing so issues surface before users are affected.
Reduce operational toil through automation, self-healing systems, and automated remediation.
Drive cost visibility and FinOps practices across cloud and LLM spending.
Integrate security into the platform through least-privilege access, secrets management, policy as code, and vulnerability management.
Use coding agents to build automation, write infrastructure code, and reason through failure modes.
Automate operational toil and incident workflows with AI in the loop.
Collaborate with the product team to provide operator-focused feedback on Blockbrain’s tools.
Stay curious about emerging AI capabilities and apply them to platform and reliability work.