AI Platform Engineer (m/f/d)

We're building the infrastructure that will make AI productive at Hellmann. Build with us. Hellmann is a globally operating logistics provider with around 10,000 employees. For us, AI isn't an add-on but a company-wide priority: we want to become an AI First Freight Forwarder. The first components of our AI infrastructure are already running. But many big decisions are still ahead of us—and those are the ones we want to make with you.

Three areas we're currently working on:

Self-service for business units. Non-engineers in the product areas should be able to build their own dashboards and tools—with AI as a tool and a secure runtime environment provided by us.

AI in engineering. We're fundamentally changing our software engineering processes: shift left, agentic engineering, spec-driven development.

Agentic AI in the core business. Perhaps the biggest opportunity of all: agents in our operational core processes, as a core way we create value and scale.

Activities

• From prototype to productive application. You build the bridge from "sketched out with Claude in Python" to "running—observed and secured—in operations."
• Selecting and integrating components. LLM gateway, container runtime, workflow and agent orchestration, observability, cost tracking. As a team, not alone.
• Snowflake as the context layer. You'll make Snowflake the home for our agents' data—for operational data, and in the longer term for ontological knowledge as well.
• Backend integration. Via API and MCP, secured through gateways, and where it makes sense, as a CLI.
• Making agents observable. Prompt, tool-use, and cost telemetry end to end, evals as part of the lifecycle, lineage from the user action through the model call to the effect in the core system.
• Security as a platform feature. Machine identities and permissions for agents, guardrails against prompt injection, clean secret management, audit trails.

Requirements

• Experience as a software or, ideally, a platform engineer
• Hands-on experience with AWS and in data engineering, ideally with Snowflake
• Have run LLM-based applications in production, or closely supported doing so
• An understanding of agents: tool use, context engineering, evaluation, observability
• High agency and the ability to make decisions and explain your reasoning clearly
• You use AI daily in your own work

What we're not looking for

• No pure data scientists and no exclusively ML engineers
• No pure DevOps engineer
• No Java developer who now wants to "dabble in AI too"

Team

You'll be part of the AI Platform Team, which is currently taking shape. It's emerging within our DXP team (Developer Experience Platform), which has already built and operates a Kubernetes-based Internal Developer Platform. The new team is deliberately kept small, senior-led, and close to the existing platform expertise.

Application Process

1. Chat via Instaffo
2. Digital interview with the hiring manager and, if applicable, team members
3. Digital / in-person interview together with the department and HR
4. Contract