Job Description
About the Role
We’re building a new AI training initiative that requires real-world engineering experience. You’ll help design and document authentic DevOps + backend scenarios based on incidents you’ve handled—outages, scaling issues, secure deployments, distributed systems challenges, and more. Your experience will directly train next-generation AI systems.
What You’ll Do
- Capture real DevOps + backend incidents and convert them into benchmark tasks
- Contribute to secure, scalable, Kubernetes-native architectures
- Work across CI/CD, observability, identity, infrastructure-as-code, and backend services
- Collaborate with our team to build realistic engineering workflows
Required Experience:
We require candidates with 2-12 years of experience and a technical degree, specializing in building secure, scalable platforms. DevOps must have deep expertise in Kubernetes, Terraform, and CI/CD, with a strong preference for secure, offline/isolated deployments. Backend Engineers must be proficient in Go/Python/Java, Docker, gRPC, and Kubernetes-native services, with ML pipeline experience a plus.
All candidates must demonstrate experience across core functional areas and technical tools, choosing at least five each from categories including: Identity & Access Management, Observability, CI/CD Pipelines, and technologies like Keycloak, GitLab CI, Kubernetes, Terraform OSS, and Prometheus + Grafana.
Strong hands-on experience in DevOps and/or Backend Engineering, including:
- Kubernetes, Terraform, CI/CD, k9s, k3s (GitLab CI preferred)
- Go / Python / Java, Docker, gRPC, Kubernetes-native services
- Experience with secure, offline/air-gapped deployments (big plus)
- Familiarity with at least five of the following:
- Identity & Access Management
- Observability (Prometheus + Grafana)
- CI/CD Pipelines
- Keycloak
- GitLab CI
- Terraform OSS
- Kubernetes tools & ecosystem
- ML/Distributed pipelines (nice to have)
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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