AI Solutions Engineer

Singtel Group; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Singtel Group is seeking an AI Solutions Engineer to design, build, and deploy enterprise AI solutions using LLMs, RAG, and AI Agents. You will develop production-ready AI apps that automate knowledge-intensive workflows and integrate with enterprise systems.

Join a team focused on secure, scalable, and trustworthy AI experiences, with opportunities to collaborate across product, engineering and business units.

Qualifications

• Bachelor’s degree in a relevant field.
• 3–5 years of software engineering experience with Python.
• Hands-on experience building LLM apps, AI Agents or RAG.
• Experience with LangChain, LangGraph, LlamaIndex or similar.
• Experience integrating APIs, databases and enterprise systems.
• Knowledge of vector databases and semantic search.

Responsibilities

• Design, develop and deploy AI agents using LLMs, RAG and prompt engineering.
• Build scalable AI workflows to automate business processes.
• Translate business requirements into practical AI solutions.
• Develop reusable prompt workflows and tool-calling capabilities.
• Build and optimise RAG pipelines connected to enterprise sources.
• Collaborate with product, engineering and business teams.

Skills

Python programming

LLM applications

RAG workflows

API integration

Vector databases

Git & CI/CD

Education

Bachelor's Degree in Computer Science, AI, Data Science or related

Tools

LangChain/LangGraph/LlamaIndex

APIs/Databases

Git & CI/CD

Docker/Kubernetes

Vector databases / semantic search

MLOps tooling

Job description

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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.
• 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.