AI Platform Engineer

SAP LeanIX

Austria

7 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

at.indeed.com

Tech stack

Artificial Intelligence Cloud Computing Cloud Computing Security Cloud Engineering Continuous Integration DevOps Identity and Access Management Python (Programming Language) Key Management Prometheus Software Engineering Software Organization

+11 more

Data Logging Cloud Platform System Spring Cloud Large Language Models Grafana Multi-Agent Systems Software Security Containerization AI Platforms Kubernetes Docker

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., * 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

Strong background 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.
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.