We are seeking a capable and pragmatic Applied AI Engineer to join our Digital Team in supporting the company's digital transformation journey. This role focuses on leveraging existing AI tools and platforms to rapidly build and deliver practical solutions that solve real business problems and improve productivity across a large, project-driven organization.
The successful candidate will act as a bridge between AI capabilities and business needs — working closely with internal stakeholders, in-house developers, and digital delivery specialists, and external technology partners to evaluate AI tools, design solution workflows, and own the end-to-end delivery of applications leveraging Large Language Models (LLMs) and related technologies. This is a hands-on, applied role, not a research position
KEY RESPONSIBILITIES
- Engage with stakeholders across departments — including site operations, procurement, project management, and corporate functions — to identify pain points and opportunities where AI can drive meaningful improvement.
- Design, prototype, and implement practical AI-powered solutions, primarily using LLMs, prompt engineering, API integrations, and workflow automation.
- Evaluate, recommend, and customize suitable AI tools or platforms; conduct light to medium coding (Python, JavaScript/TypeScript, or similar) to integrate, adapt, or extend solutions as needed.
- Collaborate with in-house developers and digital delivery specialists to integrate AI solutions into existing applications and business processes, supporting testing, deployment, and handover.
- Evaluate and collaborate with external technology specialists and AI vendors to assess emerging tools, co-develop solutions, and stay ahead of developments in the AI landscape.
- Contribute to and take ownership of the company's AI strategy and roadmap — identifying priority use cases, sequencing initiatives, and translating them into actionable delivery plans in alignment with the Head of Digital.
- Monitor solution performance, iterate on output quality and usability, and maintain compliance with company standards on data security, privacy, and responsible AI usage.
- Document AI solutions, workflows, and lessons learned to build institutional knowledge and support team capability growth.
- Stay current with developments in the AI and LLM landscape, proactively identifying new tools or approaches that could benefit the organization.
QUALIFICATIONS & EXPERIENCE
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related discipline. Candidates with a background in Civil, Structural, or Construction Engineering with demonstrated AI/software development experience are equally welcome.
- Minimum 2 years of relevant experience implementing practical AI or LLM-based solutions for business applications.
- Good working knowledge of LLMs, prompt engineering, AI workflow design, and API integration.
- Hands-on coding experience in Python, with familiarity in working with APIs and system integration.
- Strong analytical and problem-solving skills, with the ability to communicate effectively with both technical and non-technical stakeholders.
- Awareness of data privacy principles and responsible AI practices.
Preferred / Advantageous
- Familiarity with RAG (Retrieval-Augmented Generation), semantic search, vector databases, or document-based AI solutions.
- Experience with AWS Bedrock or similar managed AI/LLM platforms (e.g. Azure OpenAI, Google Vertex AI).
- Experience with AI agent frameworks or orchestration tools such as LangChain, LlamaIndex, LangGraph, or similar.
- Familiarity with cost and latency optimisation techniques for LLM-based applications (e.g. model selection, prompt caching, batching, and performance benchmarking).
- Prior experience in the construction industry or a similarly complex, project-driven environment — this will provide a meaningful advantage in understanding our business processes, site operations, and operational challenges.
