AI Solutions Engineer

NXERA SG PTE. LTD.; Singapore; Presencial; SGD 90.000 - 150.000; Jornada completa

Descripción de la vacante

NXERA SG PTE. LTD. 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 applications that automate knowledge-intensive workflows and integrate with enterprise systems.

The role focuses on creating scalable AI workflows, improving retrieval quality, and ensuring model governance with stakeholder collaboration for production rollouts.

Formación

• Bachelor's Degree in Computer Science, AI, 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.

Responsabilidades

• Design, build and deploy enterprise AI solutions using LLMs, RAG and AI Agents.
• Develop production-ready AI applications that automate knowledge-intensive workflows.
• Integrate AI solutions with enterprise systems and APIs.
• Create reusable prompt workflows, tool-calling capabilities and structured outputs.
• Build and optimize RAG pipelines connected to enterprise knowledge sources.
• Monitor and improve AI application performance and governance.

Conocimientos

Python

LLM applications

AI Agents

RAG solutions

Prompt engineering

Git

CI/CD

Container technologies

Educación

Bachelor's Degree in Computer Science

Bachelor's Degree in Artificial Intelligence

Bachelor's Degree in Data Science

Herramientas

LangChain

LangGraph

LlamaIndex

APIs

Databases

Vector databases

Semantic search

Open-source LLMs

MLOps tooling

Descripción del empleo

AI Solutions Engineer (Agentic AI)

Weare 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 optimize 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 optimize AI application performance.

Model Quality & Governance

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


• Optimize 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, modelfine-tuning or domain adaptation.