Job Summary
We are seeking an experienced and visionary Cloud-Native Architect to lead the technical architecture of our next-generation PaaS platform. The ideal candidate will have deep expertise in container orchestration, distributed systems, microservices governance, and modern DevSecOps, with a strong focus on enabling AI workloads and intelligent agent ecosystems on Kubernetes-native infrastructure.

Key Responsibilities
- Own the end-to-end architecture for our cloud-native platform, including:
- Container Infrastructure – design and optimize scalable, multi-cluster Kubernetes environments with GPU/NPU support.
- AI Compute Scheduling – enable workload-aware GPU resource orchestration, model training/inference separation, elastic scaling, and queue-based job dispatching.
- Model Deployment & Optimization – design patterns for deploying and versioning models (via KServe, Triton, TensorRT), load balancing, A/B testing, and performance tuning.
- Agent Runtime Architecture – define hosting patterns for AI agents built on frameworks like LangChain, Dify, AutoGen, including context caching, vector store binding, and multi-agent collaboration.
- Microservice Governance – service mesh integration (e.g., Istio), observability pipelines, fault injection, and zero-trust inter-service security.
- Serverless Platform – support for FaaS-based AI and edge computing workloads using Knative or OpenFaaS.
- CI/CD and GitOps – build secure and auditable pipelines for both app and model delivery using ArgoCD, Tekton, and policy engines (OPA/Kyverno).
- DevSecOps and Observability – runtime scanning, drift detection, distributed tracing, resource telemetry (including GPU stats).
- AI-native Template & Service Catalog – reusable Helm/Operator-based templates for deploying cloud-native AI workloads (e.g., Jupyter, RAG stack, LLM serving).
- Collaborate with platform engineers, SREs, ML engineers, and product managers to ensure high-performance, secure, and maintainable implementation.
- Lead architecture reviews and evolve internal standards, blueprints, and best practices across teams.
- Track and evaluate emerging technologies in the CNCF ecosystem (e.g., KubeEdge, WASM, eBPF, Gateway API) to inform architectural evolution.
- Align architectural design with compliance, scalability, and hybrid cloud goals.

Basic Qualifications:

- 8+ years of experience in software or cloud platform architecture, with 3+ years focused on cloud-native systems.

Preferred Qualifications:

- With Cloud/AI solution architecture experience would be a plus.
- Expert knowledge of Kubernetes, service mesh, container runtimes, Helm, and multi-cluster management.
- Strong experience with AI infrastructure tooling (e.g., Kubeflow, KServe, MLFlow, Airflow) and GPU/AI workload orchestration.
- Familiarity with LLM agent frameworks (LangChain, Dify, AutoGen) and vector databases (e.g., Milvus, Weaviate, FAISS).
- Proficient in designing CI/CD pipelines, GitOps flows, and DevSecOps integrations.
- Familiarity with OpenShift, Rancher, or similar enterprise container platforms is a plus.
- Strong system design and communication skills; able to align deeply technical decisions with business objectives.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

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