At Digital and Data Solutions (DDS), we develop innovative software and data-driven solutions that help customers solve complex challenges in energy, infrastructure, and sustainability. Together, we combine technology and trusted expertise to create lasting impact and accelerate the transition to a more sustainable world.
We are looking for an AI Engineer specializing in agentic systems to help design, build, productise, and evolve generative AI capabilities within Horizon, cloud platform for renewable energy asset monitoring, analytics, optimisation, and decision support.
This is a hands-on, product-focused engineering role. You will build production-grade AI agents that interact with Horizon data, analytics, algorithms, APIs, documentation, and operational workflows. The focus will be on building a role-based multi-agent system supporting users such as Asset Managers, Asset Owners, O&M Managers, Traders, and Analysts.
What You’ll Do
- Design and implement a scalable architecture for role-based AI agents, including agents supporting Asset Management, Asset Ownership, O&M, predictive maintenance, trading, and analytical workflows.
- Define agents responsibilities, tools, interaction patterns, task delegation, context sharing, and hand-offs between specialised agents.
- Integrate agents with diverse Horizon data sources, including operational time-series data, alarms, events, asset metadata, analytical results, forecasts, reports, logbooks, and technical documentation.
- Build evaluation frameworks and representative test datasets covering answer quality, groundedness, tool selection, workflow completion, hallucination risk, safety, regression, latency, and operational reliability.
- Implement observability and traceability across agent execution, including prompts, retrieved context, tool calls, model responses, decisions, failures, and user feedback.
- Deploy and operate AI services in production, working with software and platform engineers.
- Collaborate with renewable energy domain experts to ensure that agent outputs are technically meaningful, evidence-based, and appropriate for operational decision-making.
- Stay informed about developments in LLMs, agent orchestration, multimodal systems, evaluation, and AI engineering, and assess them pragmatically for production use.
What makes this role exciting: you’ll take cutting-edge 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.
ResponsibilitiesOur 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.
Requirements:
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, or a related field, or equivalent practical experience.
- Proven experience building AI agents, agentic workflows, or AI assistants, preferably in production environments.
- Experience with Retrieval-Augmented Generation (RAG), embeddings, vector search, and prompt engineering.
- Strong Python software engineering skills and experience developing production-grade applications.
- Experience integrating AI solutions with APIs, databases, and enterprise systems.
- Familiarity with Git, CI/CD, Docker, and cloud-native development practices.
- Strong communication skills and fluency in written and spoken English.
Nice to Have:
- Experience deploying AI workloads on Kubernetes.
- Experience with self-hosted LLMs and model serving.
- Familiarity with ClickHouse, MongoDB, vector databases and time-series data platforms.
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.
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