Role and responsibilities

Work directly with consulting teams to identify repeatable challenges and inefficiencies. Design and build AI-enabled workflows, automations, dashboards, and micro-applications. Develop reusable assets (prompts, templates, accelerators) for global deployment. Leverage LLMs and AI coding tools to rapidly prototype and iterate solutions. Translate business needs into practical, scalable technical solutions. Support adoption through demos, coaching, and hands-on enablement. Evaluate when solutions should be scaled, standardised, or integrated into enterprise platforms. Ensure all solutions align with data governance and responsible AI principles. Contribute to AI Accelerator best practices and innovation pipelines.

Team / description

At ERM, this isn’t experimental work on the sidelines — this is embedding AI into the core of consulting delivery, at scale, across industries and geographies. We’re hiring AI Solutions Engineers to join our global AI Accelerator team — a small, high-impact group building practical, deployable solutions that consulting teams actually use. Sustainability consulting is evolving rapidly — but delivery models are still catching up. This role exists to close that gap. You will help redefine how work gets done by embedding AI into real workflows — turning manual, fragmented processes into scalable, intelligent delivery systems. Your work won’t sit in a lab — it will be adopted across global projects, teams, and clients.

Qualifications and Skills

2–5 years building digital, automation, or AI-enabled solutions in a practical environment
Proven experience developing lightweight applications, workflows, or automation tools
Strong working knowledge of: Python, SQL, or JavaScript/TypeScript; Low/no-code tools (e.g. Power Platform, n8n, Streamlit)
Hands-on use of AI development tools (e.g. ChatGPT, GitHub Copilot, Cursor, Claude)
Experience working with APIs, integrations, and workflow orchestration
Ability to translate ambiguous business problems into working technical solutions
Strong communication skills with the ability to work directly with non-technical stakeholders
Comfortable operating in fast-moving, loosely defined environments
Degree in Computer Science, Engineering, Data Science, or related field
Experience in consulting or client-facing delivery environments (preferred)
Exposure to sustainability, ESG, EHS, or operational reporting workflows (preferred)
Familiarity with: LangChain / LangGraph / LLM orchestration frameworks; Cloud platforms (Azure, AWS, GCP, Azure OpenAI); Power BI, Tableau, or similar tools (preferred)
Understanding of responsible AI, governance, and data protection principles (preferred)
Experience building reusable solutions adopted across teams or regions (preferred)