Solutions Architect - Jakarta
1 hari yang lalu
Deskripsi pekerjaan
You will bring experience from fast-moving companies in the tech industry, paired with customer-facing skills that enable you to represent Rafay within a customer's environment and lead discussions with senior personnel. Your strong technical background will empower you to interact with and guide developers, architects, DevOps personnel, and SREs, with a particular emphasis on GPU-powered platforms and AI/ML-driven solutions.
You will collaborate closely with sales, customers, development, marketing, design, and product teams to deliver exceptional solutions to Rafay customers. As a trusted technical advisor, you will build relationships with prospects and customers through education, presentations, demonstrations, and proofs-of-concept, showcasing Rafay's market-leading Kubernetes Operations Platform, enhanced by GPU PaaS and AI/ML capabilities. This role is ambitious and stimulating, offering the opportunity to work on cutting-edge technology in the cloud-native and AI-driven computing space.
Roles & Responsibilities
- Architect Multi-Tenant Environments: Guide customers in designing secure, isolated, and scalable multi-tenant K8s environments using Rafay to manage namespace-as-a-service, resource quotas, and network policies.
- GPU Orchestration & AI/ML Ops: Lead technical workshops on slicing and sharing GPU resources (MIG/vGPU) to optimize LLM training and inference workloads.
- Platform Engineering Advocacy: Work with SRE and DevOps leadership to transition them from "manual cluster management" to a "Platform Engineering" mindset using Rafay's automation.
- Deep-Dive Troubleshooting: Act as the Tier-3 technical lead during Proofs-of-Concept (POCs), solving complex networking (CNI), storage (CSI), and identity (OIDC/RBAC) hurdles.
- Product Feedback Loop: Translate "in-the-field" multi-tenancy and GPU scheduling pain points into actionable requirements for our Engineering team.
- Kubernetes Depth: Deep understanding of K8s internals—scheduling, admissions controllers, CRDs, and the lifecycle of a Pod. You should be able to explain the difference between a Cluster-wide vs. Namespace-scoped resource in your sleep.
- Enterprise Multi-Tenancy: Proven experience managing "soft" and "hard" multi-tenancy, including Network Policies, RBAC at scale, and Hierarchical Namespaces.
- GPU & AI Infrastructure: Hands-on experience with NVIDIA GPU Operator, CUDA drivers in containers, and scheduling AI workloads (PyTorch/TensorFlow) on specialized hardware.
- Cloud-Native Networking: Solid grasp of Service Meshes (Istio/Linkerd), Ingress Controllers, and CNI providers (Cilium/Calico).
Certifications:
- CKA (Certified Kubernetes Administrator) is required
- CKS (Security) is a major plus.
Bonus Points:
- Infrastructure-as-Code Integration: Assist customers in integrating Rafay with their existing CI/CD and IaC pipelines (Terraform).
- Background in FinOps—helping customers understand the cost of unallocated GPU/CPU resources.
- Active contributor to CNCF projects or local K8s meetups.
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