AI Engineer

We’re adding an AI Engineer to the GenAI Accelerator: a hands-on builder who turns business needs into working agents. You sit between business and IT — close enough to the technology to build it yourself, close enough to the business to make sure it actually creates value. You build agents, design and control prompts, work with skills and tool calls, and stay on top of how the field is moving. What you’ll do You build agents that solve real problems — and you make sure they land. Most of your work connects three things: the value to be created, the process it lives in, and the agent that delivers it. You understand how those interact, and you build accordingly. Part of your time is forward-deployed. Beyond the large-scale process automation the team focuses on, you embed temporarily in a project or business team to build agents for their specific users and needs — getting close to the problem, shipping something useful fast, and proving value where it’s felt. Concretely, you:

• Build the agent. Develop and optimise AI agents that carry out tasks autonomously, support business processes, and make knowledge more accessible — owning prompt flows, RAG implementations, and conversation design.
• Connect value to implementation. Translate a business or user need into the right agent design, and embed it into the process so it changes how the work actually happens — not just a demo that never ships.
• Prototype fast. Build lo-fi prototypes to get real-world feedback early, then iterate toward something robust and scalable.
• Embed where needed. Drop into a specific team as a forward-deployed engineer, build for their context, and leave them better equipped.
• Keep it reliable. Safeguard accuracy, privacy, security, and quality so agents are dependable and responsible to run at enterprise scale.
• Stay ahead. Track emerging AI techniques, agent ecosystems, and integration standards (think RAG, MCP, and what comes next), and judge them on practical value. Who you work with You join a small, high-expertise team — a Product Manager and several AI-focused full-stack engineers — and work closely with the Conversational AI team, product owners, and the operation. It’s a self-directed role with real influence over how Vattenfall puts AI to work, and plenty of room to take initiative and experiment.