AI Engineer

Green Power Monitor , a DNV company, is at the heart of the global energy transformation. We use data-driven digital solutions to optimise the performance of renewable energy installations around the world. Our work contributes to a more diverse, more sustainable global energy mix.

We are looking for an AI Engineer to help create, productize and evolve generative AI solutions on Horizon, Green Power Monitor ’s cloud platform that transforms renewable energy operational data into actionable insights for monitoring, optimization, and decision‑making.

This is a hands‑on, impact‑driven role where you will build LLM‑powered agents and embed them directly into a production system used by renewable energy professionals worldwide. You will work closely with product managers and software engineers to design, deploy, and maintain production‑grade AI systems, starting with a user‑oriented AI assistant embedded in Horizon.

Over the course of the year, your work will support the strategic goal of enriching Horizon with LLM models, starting with a predictive maintenance module and evolving the platform to become more autonomous and intelligent for users, turning operational data into actionable insights.

• Connect to diverse data sources within the Horizon platform, including operational data, structured metadata, and technical documentation, and design Retrieval‑Augmented Generation (RAG) pipelines for scalable AI systems.
• Extract, transform, and structure data for optimal use with LLMs, manage embeddings, indexing, and context retrieval, and ensure AI models are grounded in accurate, real‑world information.
• Design, deploy, fine‑tune, and continuously improve production‑grade LLM and multimodal agents, optimizing prompts, mitigating hallucinations, and evaluating performance to deliver reliable, context‑aware outputs.
• Build and maintain client‑facing AI assistants and chatbots, explaining system behavior, capabilities, and limitations to both technical and non‑technical stakeholders, and integrating AI features seamlessly into Horizon workflows.
• Stay up to date with advances in generative AI, agent‑based systems, and instruction‑tuned models, experimenting with frameworks like Lang Chain and collaborating on experiments using large instruction‑tuned models.
• Collaborate closely with product and software teams to take AI solutions from concept to production, ensuring features are robust, scalable, and directly support Horizon users in monitoring, optimizing, and managing renewable energy assets.

you’ll take cutting‑edge LLM and agent‑based systems out of the lab and into production, building AI that directly supports the operation and optimization of renewable energy assets at global scale.

Our benefits package is specifically designed to support your physical, financial and social well‑being:

• Great atmosphere of working together with professionals and some of the most engaged and knowledgeable people in the industry,
• Receive guidance from colleagues through coaching, mentoring and participating in international networks,
• Advance your professional skills and technical expertise, through individual competence development plans and tailored training,
• Be part of a world growing and renowned organization with origins dating back to 1864.

• Medical Scheme,
• Commuting Allowance,
• Life Insurance,
• Pension Plan,
• Kindergarten Allowance,
• 40 hours per week with a flexible schedule. Friday
• Home working allowance (up to 2 days per week),
• 23 days of annual leave,
• Employee Referral scheme.

DNV is an Equal Opportunity Employer and gives consideration for employment to qualified applicants without regard to gender, religion, race, national or ethnic origin, cultural background, social group, disability, sexual orientation, gender identity, marital status, age or political opinion. Diversity is fundamental to our culture and we invite you to be part of this diversity.

• Master’s degree or equivalent experience in Mathematics, Data Science, Computer Science, Machine Learning, or a related field,
• Hands‑on experience with Large Language Models (LLMs) or…