AI Engineer – LLMs, AI Agents & ML Solutions

HG Infotech Pte. Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

HG Infotech Pte. Ltd. is seeking an AI Engineer specializing in Large Language Models (LLMs), autonomous AI agents, and RAG architectures to design and deploy enterprise-grade AI solutions for clients across Singapore, Malaysia, and ASEAN.

The role focuses on building intelligent workflow automation tools and predictive ML systems for global enterprise clients. You will work with LangChain, LlamaIndex, AutoGen and CrewAI, deploy models to cloud platforms, and ensure governance and security.

Qualifications

• 3–7 years of hands-on experience in AI, ML, NLP, and DL engineering.
• Strong Python and ML framework expertise.
• Experience deploying AI models in cloud and CI/CD pipelines.

Responsibilities

• Architect, train, fine-tune, and deploy custom LLMs and autonomous AI workflows.
• Implement enterprise RAG (Retrieval-Augmented Generation) pipelines with vector databases.
• Design end-to-end ML models for predictive analytics, NLP, and automation.
• Develop RESTful & gRPC APIs for AI models using Python, FastAPI, PyTorch, and Hugging Face Transformers.
• Optimize inference latency and cloud deployment on Azure OpenAI / AWS SageMaker.
• Ensure enterprise AI governance, prompt security, and guardrails.
• Collaborate with enterprise architects to translate workflows into scalable AI systems.

Skills

AI/ML engineering

NLP

Python

PyTorch

Transformers

LangChain

LlamaIndex

Autonomous Agents

Vector Databases

MLOps

CI/CD

Weights & Biases

Education

Bachelor’s or Master’s degree in CS/AI

Tools

Pinecone

Qdrant

Milvus

pgvector

Azure OpenAI

AWS SageMaker

vLLM

LangChain

LlamaIndex

CrewAI

AutoGen

LangGraph

Hugging Face

Job description

HG Infotech is looking for an AI Engineer specializing in Large Language Models (LLMs), Autonomous AI Agents, RAG (Retrieval-Augmented Generation) architectures, and Machine Learning workflows. In this role, you will design and deploy enterprise-grade AI agents, intelligent workflow automation tools, and predictive ML systems for our global enterprise clients across Singapore, Malaysia, and ASEAN.

Responsibilities

• Architect, train, fine-tune, and deploy custom LLMs and autonomous AI Agent workflows using LangChain, LlamaIndex, AutoGen, or CrewAI.
• Implement enterprise RAG (Retrieval-Augmented Generation) pipelines integrated with Vector Databases (Pinecone, Qdrant, ChromaDB, pgvector).
• Design and build end-to‑end Machine Learning models for predictive analytics, natural language processing (NLP), and process automation.
• Develop production RESTful & gRPC APIs wrapping AI models using Python, FastAPI, PyTorch, and Hugging Face Transformers.
• Optimize AI model inference latency, quantization, and token efficiency for cloud deployments on Azure AI / AWS SageMaker.
• Ensure enterprise AI governance, prompt security, hallucination mitigation, guardrails (NeMo Guardrails), and compliance standards.
• Collaborate with enterprise solution architects and client leaders to translate business workflows into scalable AI agent systems.

Qualifications

• 3–7 years of hands‑on experience in AI, Machine Learning, NLP, and Deep Learning engineering.
• Deep expertise with Python, PyTorch / TensorFlow, Hugging Face Transformers, LangChain, and LlamaIndex.
• Hands‑on experience building Autonomous AI Agents (CrewAI, AutoGen, LangGraph) and function‑calling architectures.
• Solid experience with Vector Databases (Pinecone, Qdrant, Milvus, pgvector) and embedding techniques.
• Production experience deploying AI models on Azure OpenAI, AWS SageMaker, or vLLM containerized microservices.
• Strong foundation in MLOps, model evaluation, monitoring (MLflow, Weights & Biases), and CI/CD for AI systems.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related technical field.