Hiring: Senior GenAI Engineer (LLM, RAG & Azure AI)
Singapore | Permanent
We are looking for a hands-on GenAI Engineer with strong experience in LLMs, RAG Architecture, Azure AI Services, and end-to-end ML pipeline development.
Key Responsibilities
- Design, develop, and deploy enterprise-grade Generative AI solutions.
- Build and optimize RAG architectures, embeddings, chunking strategies, and retrieval mechanisms.
- Own end-to-end ML pipelines from document ingestion, processing, serving, monitoring, and optimization.
- Design and implement Azure-based data processing pipelines including OCR, document intelligence, text extraction, and data transformation.
- Develop and integrate APIs and backend services to support AI-powered applications.
- Design and optimize relational and NoSQL databases such as Azure SQL and Cosmos DB.
- Deploy, monitor, and maintain ML and GenAI solutions in production environments.
- Collaborate with business and technical stakeholders to deliver scalable AI solutions.
- Ensure solutions meet enterprise requirements for security, scalability, reliability, and performance.
Requirements
7+ years of experience in AI, Machine Learning, Data Science, or Software Engineering
Hands-on experience with:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Chunking Strategies
- Embeddings
- Vector Search / Semantic Search
- Data Retrieval Mechanisms
Strong experience in:
- Python Development
- Azure AI Services
- Azure OpenAI
- Azure SQL
- Cosmos DB
- REST APIs
- Cloud-Native Architecture
Experience owning end-to-end ML pipelines:
- Raw Document Ingestion
- Processing & Transformation
- Model Serving
- Monitoring & Optimization
Experience with:
- OCR / Document Intelligence
- Structured & Unstructured Data Processing
- MLOps & Production Deployments
- Security, Cost Optimization & Scalability
Nice to Have
LangChain / LangGraph / LlamaIndex
Agentic AI Frameworks
Azure Entra ID (Azure AD)
OAuth2 / JWT
Azure Key Vault
Agile / Scrum Environment
If you have built and deployed production-grade AI solutions leveraging LLMs and RAG architectures, we would love to hear from you.