Ai engineer renewable energy assets

Описание

DNV is an independent expert in assurance and risk management. Its Energy Systems division helps customers navigate the transition to a decarbonized and sustainable energy future by assuring that energy systems operate safely and effectively through increasingly digital solutions. Digital and Data Solutions develops software and data-driven solutions for energy, infrastructure, and sustainability, including Horizon, a cloud platform for renewable energy asset monitoring, analytics, optimization, and decision support.

• Design and implement scalable architecture for role-based AI agents supporting asset management, asset ownership, O&M, predictive maintenance, trading, and analytical workflows
• Define agent responsibilities, tools, interaction patterns, task delegation, context sharing, and hand-offs between specialized agents
• Integrate agents with 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 with software and platform engineers
• Collaborate with renewable energy domain experts to ensure agent outputs are technically meaningful, evidence-based, and appropriate for operational decision-making
• Assess developments in LLMs, agent orchestration, multimodal systems, evaluation, and AI engineering for production use

• 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, 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
• Ownership of projects, clear communication of complex AI concepts to technical and non-technical stakeholders, and adaptability in collaborative, fast-moving environments
• Nice to have:
  Experience deploying AI workloads on Kubernetes, self-hosted LLMs and model serving, Click House, MongoDB, vector databases, and time-series data platforms

• Medical Scheme
• Life Insurance
• Pension Plan
• Home working allowance of up to 2 days per week
• Employee Referral scheme
• Coaching, mentoring, international networks, individual competence development plans, and tailored training
• Background checks will be conducted on all final candidates as part of the offer process