Platform Integration / Infrastructure Engineer

Do you enjoy making complex platforms work reliably in real enterprise environments, where identity, networking, certificates, storage, proxies, observability, and deployment policies all matter?

PortBlueSky is supporting a major multinational enterprise in scaling a widely adopted open-source agentic AI platform for large corporate environments. We are looking for a Platform Integration / Infrastructure Engineer who can own cross-cutting platform patterns and help make the platform ready for client-owned clusters, multi-cloud environments, and production operations.

This role is ideal for someone who likes the "boring but critical" parts of infrastructure: bootstrap order, permissions, APIService readiness, webhook certificates, chart upgrades, storage classes, health checks, runbooks, and everything else that determines whether a platform actually works outside a demo., * Own enterprise deployment patterns: Design repeatable, production-ready Kubernetes deployment models across development, staging, production, and client-owned environments.

• Make the platform fit real client infrastructure: Integrate with enterprise identity, ingress, certificates, storage, secrets, observability, service meshes, external managed services, and internal governance models.
• Improve Kubernetes installation and operations: Work with Helm, cert-manager, Gateway API/Ingress, APIService installation, NetworkPolicy, RBAC, service accounts, custom CAs, proxies, and TLS constraints.
• Build platform hooks and integration paths: Support authentication chains, service bus/eventing integrations, workload identity, managed identity, cloud-native secrets, and model gateway integration.
• Support multi-cloud client patterns: Help integrate the platform with Azure, AWS, GCP, Databricks, S3-compatible storage, managed Postgres, OTEL collectors, Langfuse/Phoenix, and enterprise model gateways.
• Create reusable deployment assets: Scaffold Helm values, Terraform modules, GitOps examples, deployment templates, reference blueprints, and operational documentation.
• Advise client teams: Guide clients on cluster administration, identity management, GitOps layout, observability, operational ownership, and production rollout planning.
• Increase operational safety: Reduce failure modes around install order, certificates, CRDs, APIService availability, permissions, storage, upgrades, and runtime health.

What We Offer

• A serious enterprise platform challenge: Work on infrastructure patterns for an open-source AI platform being scaled into demanding multinational environments.
• Highly senior colleagues: Join a developer-led company that publicly emphasizes top-tier technical experts, challenging enterprise projects, and strong communication.
• Remote-first working culture: Work flexibly from anywhere, with conditions designed by developers for developers.
• High technical leverage: Your work will shape how the platform is installed, operated, secured, and adopted across real client environments.
• Room for advisory leadership: Help client teams make sound architecture and operations decisions, not just ship configuration files.

You are an experienced platform or infrastructure engineer with:

• Strong experience designing HA Kubernetes deployments across multiple environments and ownership models.
• Deep familiarity with how enterprises provision Kubernetes, identity, ingress, certificates, storage, secrets, observability, service meshes, and managed services.
• Strong practical knowledge of Helm, cert-manager, Gateway API/Ingress, APIService installation, NetworkPolicy, RBAC, service accounts, custom CAs, enterprise proxies, and TLS.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• A productionization mindset focused on repeatability, safety, upgradeability, and operational clarity.
• The ability to communicate clearly with both engineering teams and client platform teams.
• Fluent English and comfort working in a remote, international environment.
• EU residency and permission to work in the EU., * Experience with Databricks, S3-compatible object storage, managed Postgres, OTEL collectors, Langfuse, Phoenix, or enterprise model gateways.
• Familiarity with agentic AI platforms, workflow orchestration, MCP, A2A, or Kubernetes-native AI runtimes.
• Experience writing runbooks, platform blueprints, client-facing architecture documents, or GitOps reference implementations.
• Consulting or forward-deployment experience in large enterprise environments.