AI Engineer - Agentic Systems

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.