AI Solutions Engineer

Role Overview

• Build new platform capabilities from architectural designs, translating security, governance, and infrastructure requirements into production-grade infrastructure-as-code.
• Design and build the platform security and secrets management layer, ensuring all workloads operate with least-privilege credentials and certificates issued through a governed PKI hierarchy.
• Implement and enforce security policy across the cluster using admission control, covering workload configuration, image standards, network traffic, and resource constraints.
• Build and establish the platform observability stack, providing consistent log aggregation, metrics, distributed tracing, and alerting across all platform components.
• Design and implement GitOps delivery automation, ensuring all platform changes flow through version-controlled, auditable pipelines with drift reconciliation.
• Build and configure workload autoscaling, ensuring AI workflow workers scale efficiently and cost-effectively in response to demand.
• Implement the AI model routing and gateway layer, enabling governed, auditable routing of model traffic with per-consumer rate limiting.
• Own the day-to-day operational health of the platform: monitor for issues, respond to incidents, conduct root-cause analysis, and implement lasting remediation.
• Maintain the health of platform data services — database cluster, job queue, and object storage — including backup schedules, failover testing, and capacity management.
• Monitor and tune autoscaling and resource configuration as workload patterns evolve, ensuring the platform scales responsively without over-provisioning.
• Manage secrets rotation, certificate lifecycle, policy drift detection, and identity configuration as ongoing operational responsibilities.
• Proactively identify and resolve technical debt — manual processes, undocumented configurations, legacy credential management, and gaps in observability coverage.

Requirements

• Hands-on production delivery experience, not just conceptual familiarity.
• Kubernetes — production cluster operation (RKE2, EKS, GKE, or equivalent); Helm, RBAC design, multi-namespace workload management.
• Secrets management — production deployment of a secrets management platform (HashiCorp Vault or equivalent), covering PKI, dynamic credentials, and workload secrets injection.
• Policy-as-code — admission control policy authoring and enforcement in production Kubernetes environments (OPA/Rego, Kyverno, or equivalent).
• GitOps — Fleet, ArgoCD, Flux, or equivalent at production scale; declarative drift reconciliation, rollback strategy, multi-environment targeting.
• Observability stack — log aggregation, log pipeline design, distributed tracing (OpenTelemetry or equivalent), and metrics dashboards (Prometheus/Grafana or equivalent).
• API gateway engineering — production deployment and operation of an API or AI gateway (Kong, Envoy, or equivalent); rate limiting, plugin/policy authoring, route management.
• Linux platform engineering — networking fundamentals, TLS and PKI, CSI storage operations, container runtime.

Tech Stack

• Flux
• Grafana
• Kubernetes
• Linux
• Prometheus
• Vault

Benefits

• We empower you to be bold, driving your career to create the future you want.
• We celebrate and reward your achievements.
• SUSE is a dynamic environment that is evolving rapidly, thus requiring agility, strong entrepreneurship and an open mind.
• A compelling opportunity for the right person to join us as we continue to scale and prosper.
• Freedom to be yourself in a global community of unique individuals – like you – with different backgrounds, talents, skills and perspectives.
• A truly open community where everyone is welcome, has a voice and is encouraged to reach their full potential regardless of age, gender, race, nationality, disability, sexual orientation, religion, or any other characteristics.