人工智能平台工程师 (m/f/d)
AI Platform Engineer (m/f/d)
作为AI平台工程师，你将加入团队，推动SAP Fioneer在银行部门的生成式AI计划。与AI工程师和软件开发人员紧密合作，你将设计、构建并运营支撑企业级AI解决方案的云平台、基础设施和运维能力。该职位提供使用现代云原生技术的机会，同时为AI应用的安全、可扩展和可靠部署到生产环境做出贡献。
关键职责
- 设计、构建并运营企业级AI解决方案所需的基础架构和平台能力。
- 使用Docker和Kubernetes开发和维护容器化应用及部署环境。
- 推动安全、可扩展性、可靠性、可观测性和运维卓越性的生产就绪性。
- 设计并实现具有强隔离和治理概念的多租户架构。
- 建立监控、日志、追踪、告警和运维仪表盘。
- 构建和维护CI/CD流水线、发布流程和基础设施即代码。
- 定义并实施安全控制、密钥管理、身份集成和安全部署实践。
- 与AI工程师和软件开发人员协作，将AI解决方案从原型过渡到生产环境。
- 直接参与应用开发，重点关注平台能力、集成、运维工具和与基础设施相关的代码。
- 支持与云基础设施、安全、运维和可维护性相关的架构决策。
- 推动AI解决方案中平台标准化、自动化和运维最佳实践。
要求
- (商业)信息学、(商业)数学、计算机科学、物理、工程专业学位，对金融服务业领域感兴趣。
- 2-3年平台工程、DevOps或云工程经验。
- 具有运行生产级云原生应用的经验。
- 精通Kubernetes、Docker和容器编排。
- 具有CI/CD、基础设施即代码和自动化框架的经验。
- 熟悉可观测性平台，如Langfuse、OpenTelemetry、Grafana、Prometheus或Azure Monitor者优先。
- 具有云安全、身份管理和多租户架构的经验。
- 熟悉Python和现代软件开发实践。
查看英文原文
As an AI Platform Engineer, you will join the team driving SAP Fioneer's Generative AI initiative within our Banking division. Working closely with AI Engineers and Software Developers, you will design, build, and operate the cloud platform, infrastructure, and operational capabilities that power enterprise-grade AI solutions. This role offers the opportunity to work with modern cloud-native technologies while contributing to the secure, scalable, and reliable deployment of AI applications into production.
Key Responsibilities
- Design, build, and operate the infrastructure and platform capabilities required for enterprise-grade AI solutions.
- Develop and maintain containerized applications and deployment environments using Docker and Kubernetes.
- Drive production readiness across security, scalability, reliability, observability, and operational excellence.
- Design and implement multi-tenant architectures with strong isolation and governance concepts.
- Establish monitoring, logging, tracing, alerting, and operational dashboards.
- Build and maintain CI/CD pipelines, release processes, and Infrastructure-as-Code.
- Define and implement security controls, secrets management, identity integration, and secure deployment practices.
- Collaborate with AI Engineers and Software Developers to transition AI solutions from prototype to production.
- Contribute directly to application development with a focus on platform capabilities, integrations, operational tooling, and infrastructure-related code.
- Support architecture decisions related to cloud infrastructure, security, operations, and maintainability.
- Drive platform standardization, automation, and operational best practices across AI solutions.
Requirements
- Degree in (Business) Informatics, (Business) Mathematics, Computer Science, Physics, Engineering and interest in the area of financial services.
- 2-3 years of experience in Platform Engineering, DevOps, or Cloud Engineering.
- Experience operating production-grade cloud-native applications.
- Hands-on expertise with Kubernetes, Docker, and container orchestration.
- Experience with CI/CD, Infrastructure-as-Code, and automation frameworks.
- Knowledge of observability platforms such as Langfuse, OpenTelemetry, Grafana, Prometheus, or Azure Monitor is considered an asset.
- Experience with cloud security, identity management, and multi-tenant architectures.
- Familiarity with Python and modern software development practices.
- Understanding of AI platforms, LLM applications, agent frameworks, or RAG systems is beneficial.
- Strong troubleshooting and operational mindset.
Benefits
We offer a comprehensive benefits package that includes occupational pension provisions, support for health and wellbeing, various mobility options like bike leasing and transportation allowances, as well as additional perks such as celebration rewards, meal programs, jubilee recognition, and relocation reimbursement.
Originally posted on Himalayas