AI Solutions Engineer
Summary
Design and deploy AI agents using LLMs, RAG, and prompt engineering to automate enterprise workflows and integrate with internal systems for a next-gen data center operator.
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!”
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.
- 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.
- Exposure to MLOps, model fine‑tuning or domain adaptation.