AI Platform Engineer

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Join an organization at the forefront of AI and Data Analytics transformation, where Artificial Intelligence is being embedded across enterprise platforms to drive innovation, operational excellence, and business value. This role offers the opportunity to build and scale modern AI platforms that enable next-generation AI, Machine Learning, and Generative AI solutions across the enterprise. If you are passionate about cloud-native technologies, AI infrastructure, and platform engineering, this is your chance to contribute to a large-scale AI transformation initiative. Key Responsibilities Support the implementation and enhancement of an enterprise AI Platform running on cloud-native infrastructure using Red Hat OpenShift or equivalent Kubernetes platforms. Build and integrate AI platform capabilities including API Gateway, Retrieval-Augmented Generation (RAG) pipelines, AI agent orchestration, model serving, and observability components. Deploy, configure, and manage Kubernetes/OpenShift clusters across CPU and GPU environments. Automate infrastructure provisioning and platform operations using Infrastructure-as-Code (IaC), CI/CD pipelines, and DevOps best practices. Integrate AI platform services with enterprise infrastructure including networking, storage, load balancers, backup, and security services. Implement platform security controls including Identity Access Management (IAM), Active Directory integration, SIEM, Endpoint Detection Response (EDR), and Next Generation Firewalls (NGFW). Support AI/ML workloads including Large Language Models (LLMs), Generative AI applications, RAG architectures, and agent-based AI frameworks. Monitor platform health, optimize performance, manage logging, and support capacity planning to ensure high availability and scalability. Collaborate closely with AI engineers, data scientists, DevOps engineers, and enterprise technology teams to deliver secure and reliable AI platform capabilities. Continuously evaluate emerging cloud-native and AI platform technologies to improve platform capabilities and operational efficiency. Key Requirements: Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline. Minimum 3 years of experience in Platform Engineering, Cloud Infrastructure, Kubernetes, DevOps, or AI/Data Platform Engineering. Hands-on experience with Kubernetes/OpenShift , including cluster deployment, networking, operators, and security. Experience with Infrastructure-as-Code (Terraform, Ansible, or similar tools). Familiarity with CI/CD pipelines and DevOps automation practices. Good understanding of enterprise networking, cloud infrastructure, and security principles. Exposure to AI platform technologies including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) AI inference/model serving Agentic AI frameworks (preferred) Knowledge of monitoring and observability tools for distributed platforms. Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and stakeholder collaboration abilities. Passion for learning emerging AI and cloud-native technologies. Preferred Qualifications Red Hat OpenShift Certification. Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD). Experience working with GPU-enabled Kubernetes environments. Exposure to MLOps platforms and AI infrastructure. Experience supporting enterprise-scale AI or cloud transformation initiatives. Why Join Us Be part of a large-scale AI transformation initiative. Work with cutting-edge AI, Generative AI, and cloud-native technologies. Collaborate with highly skilled engineering and AI teams. Opportunity to shape enterprise AI platforms that power next-generation business capabilities. Continuous learning and professional development in one of the fastest-growing technology domains. Originally posted on Himalayas

加入一个处于AI和数据分析转型前沿的组织，人工智能正被嵌入企业平台，以推动创新、卓越运营和业务价值。该职位提供构建和扩展现代AI平台的机会，使下一代AI、机器学习和生成式AI解决方案能够在整个企业范围内落地。如果您对云原生技术、AI基础设施和平台工程充满热情，这是您参与大规模AI转型计划的机会。

关键职责

支持基于Red Hat OpenShift或同等Kubernetes平台运行的云原生基础设施上的企业AI平台的实施和增强。

构建和集成AI平台能力，包括API Gateway、检索增强生成（RAG）管道、AI代理编排、模型服务和可观测性组件。

在CPU和GPU环境中部署、配置和管理Kubernetes/OpenShift集群。

使用基础设施即代码（IaC）、CI/CD管道和DevOps最佳实践，自动化基础设施配置和平台运维。

将AI平台服务与企业基础设施集成，包括网络、存储、负载均衡器、备份和安全服务。

实施平台安全控制，包括身份访问管理（IAM）、Active Directory集成、SIEM、端点检测响应（EDR）和下一代防火墙（NGFW）。

支持AI/ML工作负载，包括大型语言模型（LLMs）、生成式AI应用、RAG架构和基于代理的AI框架。

监控平台健康状态、优化性能、管理日志记录并支持容量规划，以确保高可用性和可扩展性。

与AI工程师、数据科学家、DevOps工程师和企业技术团队紧密协作，交付安全可靠的AI平台能力。

持续评估新兴云原生和AI平台技术，以改进平台能力和运营效率。

关键要求：

计算机科学、信息技术、工程或相关学科的学士学位。

至少3年平台工程、云基础设施、Kubernetes、DevOps或AI/数据平台工程经验。

具备Kubernetes/OpenShift的实操经验，包括集群部署、网络、Operator和安全。

具备基础设施即代码（Terraform、Ansible或类似工具）经验。

熟悉CI/CD管道和DevOps自动化实践。

对企业网络、云基础设施和安全原则有良好理解。

接触过AI平台技术，包括：

大型语言模型（LLMs）

检索增强生成（RAG）

AI推理/模型服务

代理式AI框架（优先）

了解分布式平台的监控和可观测性工具。

较强的分析、故障排除和问题解决能力。

出色的沟通和利益相关者协作能力。

对学习新兴AI和云原生技术充满热情。

优先资格

Red Hat OpenShift认证。

Certified Kubernetes Administrator（CKA）或Certified Kubernetes Application Developer（CKAD）。

具备GPU-enabled Kubernetes环境的工作经验。

接触过MLOps平台和AI基础设施。

有支持企业级AI或云转型计划的经验。

为什么加入我们

参与大规模AI转型计划。

接触前沿AI、生成式AI和云原生技术。

与高技能工程和AI团队协作。

有机会塑造赋能下一代业务能力的企业AI平台。

在增长最快的技术领域之一中持续学习和职业发展。

最初发布于Himalayas

⚑ 岗位信息收录自公开招聘页（Himalayas），以雇主官网为准