AI Solutions Engineer

Nxera; Singapore; On-site; Confidential; Full time

Job summary

Nxera is seeking an AI Software Engineer to design and deploy AI agents, RAG pipelines and enterprise-grade AI solutions in Singapore. The role focuses on translating business needs into scalable AI workflows and secure tool-calling capabilities.

You will collaborate with product, engineering and business teams to deliver AI-powered solutions, integrate with enterprise systems and ensure production readiness with governance and testing.

Qualifications

• Bachelor's degree in CS/AI/Data Science or related field.
• 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.

Responsibilities

• 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.

Skills

Python

LLM applications

RAG solutions

LangChain

LangGraph

LlamaIndex

API integration

Vector databases

Git & CI/CD

Containerization

Education

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

Tools

LangChain

LangGraph

LlamaIndex

Git

Docker

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!”

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.