At a Glance
- Tasks: Create and evolve generative AI solutions for renewable energy data on our cloud platform.
- Company: Join GreenPowerMonitor, a leader in the global energy transformation.
- Benefits: Flexible hours, remote work, professional development, and comprehensive health benefits.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Make a real impact by building AI that optimises renewable energy operations worldwide.
- Qualifications: Master’s degree in relevant fields and hands-on experience with LLMs or generative AI.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About Energy Systems: We help customers navigate the complex transition to a decarbonized and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments to navigate the many complex, interrelated transitions taking place globally and regionally, in the energy industry. GreenPowerMonitor, 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 LLM Engineer to help create, productize and evolve generative AI solutions on Horizon, GreenPowerMonitor’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.
What You’ll Do:
- 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 LangChain 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.
What makes this role exciting: 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.
Other than you can expect:
- 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.
Requirements:
- 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 generative AI systems.
- Experience with RAG pipelines, embeddings, and prompt optimization.
- Strong understanding of Transformer architectures and fine‑tuning.
- Proficiency in Python.
- Familiarity with CI/CD, Docker, Kubernetes (K8s), and Git is a plus.
- Fluency in written and spoken English.
You are curious, adaptable, and proactive, thriving in collaborative, fast‑moving environments. You take ownership of projects, communicate complex AI concepts clearly to technical and non‑technical stakeholders, and enjoy solving challenging real‑world problems.
As part of the interview process, we ask you to submit a short report or demo of an AI agent you’ve built. This is your chance to showcase your hands‑on skills and highlight your creativity.
Security and compliance with statutory requirements in the countries in which we operate is essential for DNV. Background checks will be conducted on all final candidates as part of the offer process, in accordance with applicable country‑specific laws and practices.
LLM Engineer employer: DNV Germany Holding GmbH
Contact Detail:
DNV Germany Holding GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLMs and AI. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to LLM engineering. Think about how you’d explain complex concepts to non-techies – clarity is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at GreenPowerMonitor.
We think you need these skills to ace LLM Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the LLM Engineer role. Highlight your experience with LLMs, RAG pipelines, and any relevant projects that showcase your skills. We want to see how you fit into our mission of transforming renewable energy!
Showcase Your Skills: Don’t hold back on demonstrating your hands-on experience! Include specific examples of AI agents or systems you've built, especially if they relate to generative AI. This is your chance to shine and show us what you can bring to the table.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain complex concepts, as you'll need to communicate effectively with both technical and non-technical stakeholders in this role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, it shows us you're serious about joining our team at GreenPowerMonitor!
How to prepare for a job interview at DNV Germany Holding GmbH
✨Know Your Stuff
Make sure you brush up on your knowledge of Large Language Models and generative AI systems. Be ready to discuss your hands-on experience with RAG pipelines, embeddings, and prompt optimisation. This is your chance to show that you’re not just familiar with the theory but can apply it in real-world scenarios.
✨Showcase Your Projects
Prepare a short report or demo of an AI agent you've built, as this is part of the interview process. Highlight your creativity and problem-solving skills. Make sure to explain the challenges you faced and how you overcame them, as this will demonstrate your ability to think critically and adapt.
✨Communicate Clearly
You’ll need to explain complex AI concepts to both technical and non-technical stakeholders. Practice simplifying your explanations without losing the essence of what you want to convey. This skill is crucial for collaborating with product managers and software engineers.
✨Stay Current
Keep yourself updated on the latest trends in generative AI and agent-based systems. Familiarise yourself with frameworks like LangChain and be prepared to discuss how you would experiment with these technologies. Showing that you’re proactive about learning will impress your interviewers.