AI Solutions Engineer

Company not disclosed

Singapore, Singapore
Salary not specified
Posted
Full-time
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Job Description

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. Hiring Manager: Sivasankar Subbiah Talent Acquisition Manager: Kong Chiew Yen

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