AI Solutions Engineer

Passionate about making a real impact? Be at the forefront of the data centre (DC) industry with a unique focus on sustainability, connectivity and AI which sets us apart as the next generation DC operator. You will also get to gain invaluable experience in a fast-growing industry that is powering the digitalisation wave. Be empowered to co-create the future with our dynamic teams!”

We are seeking an AI Solutions Engineer (Agentic AI) to design, build and deploy enterprise AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI Agents. You will develop production-ready AI applications that automate knowledge-intensive workflows, integrate with enterprise systems and deliver secure, scalable and trustworthy AI experiences.

How You will Make An Impact:

AI Solution Development

• Design, develop and deploy AI agents using LLMs, RAG and prompt engineering.

• Build scalable AI workflows that automate enterprise business processes.

• Translate business requirements into practical AI solutions.

• Develop reusable prompt workflows, tool-calling capabilities and structured outputs.

Knowledge & RAG Engineering

• Build and optimise RAG pipelines connected to approved enterprise knowledge sources.

• Improve retrieval quality through chunking, embeddings, indexing and metadata strategies.

• Maintain trusted knowledge bases and ensure source-grounded AI responses.

AI Platform & Integration

• Integrate AI applications with enterprise systems, APIs, databases and internal platforms.

• Develop secure tool-calling capabilities and support deployment into production.

• Monitor and optimise AI application performance.

Model Quality & Governance

• Design evaluation frameworks to measure response quality, retrieval accuracy and hallucination risks.

• Optimise prompts, guardrails and model performance.

• Support governance, version control and human-in-the-loop review processes.

Stakeholder Collaboration

• Partner with product, engineering and business teams to deliver AI solutions.

• Support demonstrations, UAT, production rollout and technical documentation.

• Communicate technical concepts clearly to technical and non-technical stakeholders.

Skills for Success:

• Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science or related discipline.

• 3–5 years of software engineering experience with Python.

• Hands-on experience building LLM applications, AI Agents or RAG solutions.

• Experience with LangChain, LangGraph, LlamaIndex or similar AI frameworks.

• Experience integrating APIs, databases and enterprise systems.

• Knowledge of vector databases, semantic search and prompt engineering.

• Experience with Git, CI/CD and container technologies.

Preferred Skills:

• Experience with Azure OpenAI, AWS Bedrock or Google Vertex AI.

• Knowledge of MCP (Model Context Protocol) or AI agent orchestration.

• Experience deploying open-source LLMs (e.g. vLLM, Ollama).

• Exposure to MLOps, model fine-tuning or domain adaptation.

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