AI Platform Engineer (m/f/x)

Das ist der Job

Implement comprehensive LLM observability, logging, and alerting systems using tools like Datadog and Langfuse.

Darum lohnt es sich

Strong problem‑solving skills, a sense of humor, and the ability to thrive in an ego‑free environment as an embedded platform expert within a cross‑functional Data Science and AI team.

Benefits Be part of one of the fastest‑growing and most visible Fintech startups in Europe, creating innovative services that have a substantial impact on the lives of our customers Work with an international, diverse, inclusive, and ever‑growing team that loves creating the best products for our clients Be productive with the latest hardware and tools Learn and grow by joining our in‑house knowledge sharing or career development sessions and spending your individual Education Budget Learn and experience German culture first hand by joining our free German language classes International relocation support is provided if required Opportunity to work from abroad Benefit from an attractive compensation package and from the company pension scheme Monthly contribution of 50% for the ‘Deutschland Jobticket’ Say goodbye to order commissions and say hello to your complimentary subscription of Scalable Capital's PRIME+ Broker Enjoy flexible and discounted sports activities with Urban Sports Club #J-18808-Ljbffr AI Platform Engineer As an AI Platform Engineer embedded within our Data Science and AI tribe, you will design and maintain the foundational infrastructure that enables our AI Software Engineers to build and scale generative AI applications.

You will build our internal AI provisioning platform, focusing on seamless model access, observability, and strict governance. In this role, you will ensure our AI integrations are secure, performant, and cost‑effective, providing the robust backbone required for our agentic and LLM‑driven workflows.

Responsibilities Develop and maintain an internal AI provisioning platform to streamline access to various LLMs & MCP Servers (e.g., via LiteLLM). Enforce model governance, ensuring security, data privacy, rate limiting, and strict LLM API cost management.

Collaborate closely with embedded AI Software Engineers to support cloud‑native architectures and agentic workflow integrations. Build and maintain infrastructure for monitoring the reliability and performance of production AI systems. Qualifications Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

Several years of professional experience in Platform Engineering, DevOps, SRE, or backend software development. Strong experience and confidence working with cloud infrastructure (AWS preferred) and Infrastructure as Code (Terraform).

Proficiency in at least one programming language (e.g., Python, Go) and experience with CI/CD pipelines and containerization (e.g., Docker). Solid understanding of API cost management, rate limiting, security best practices, and data privacy for AI models.

Experience with, or a strong willingness to learn, LLM gateways, observability platforms, and telemetry (e.g., LiteLLM, Langfuse, Datadog).