As an AI Architect, you will own the technical architecture of GenAI and LLM solutions, translating requirements into scalable blueprints and driving responsible AI practices.
AI Platform Engineer (m/f/d)
π Description
- 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.
π οΈ 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.
β¨ Benefits
- A comprehensive benefits package that includes occupational pension provisions
- Support for health and wellbeing
- As well as additional perks such as celebration rewards
- Relocation reimbursement
Full job description
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.
Similar jobs
Search more AI Engineer jobsDeployed Engineer (Federal)
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent.
As an AI Engineer, you'll bridge business challenges and technical solutions, working directly with clients to design and implement AI products that deliver real value.
As an AI Engineer, you'll build and operate backend systems that enhance AI-powered product capabilities, collaborating with cross-functional teams to ensure reliable and effective member communications.
Machine Learning Applied Scientist - ADAS Online
As a machine learning applied scientist, you will enhance models for in-vehicle spatial awareness, tackling complex engineering challenges in a dynamic team environment.
