Senior GenAI Knowledge Architect for Enterprise AI

Avensys Consulting; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Avensys Consulting is seeking a Senior AI Knowledge Engineer to design and deploy enterprise GenAI knowledge systems, including RAG pipelines, document ingestion and embeddings. You will build production-ready AI services and integrate with enterprise applications.

The role requires deep AI/ML expertise, hands-on work with LangChain, vector databases and cloud platforms (Azure/AWS/GCP). Collaboration on governance and scalable AI delivery is essential.

Qualifications

• 8+ years of software/data/AI engineering experience.
• 4+ years in AI/ML, GenAI, Rag or Knowledge Engineering.
• Experience with LangChain, LangGraph, LlamaIndex or Semantic Kernel.
• Experience with vector databases and cloud AI services (Azure/AWS/GCP).

Responsibilities

• Build enterprise GenAI knowledge systems, RAG pipelines and AI assistants/agents.
• Develop knowledge ingestion, embeddings, vector/semantic/hybrid search and retrieval solutions.
• Integrate knowledge systems with LLMs, AI agents and enterprise applications.
• Implement knowledge grounding, access-controlled retrieval and hallucination mitigation.
• Develop APIs and production-ready AI knowledge services using Python.
• Work with vector databases, knowledge graphs and AI frameworks.
• Deploy and optimize solutions on Azure, AWS or GCP.

Skills

8+ years exp

4+ years AI/ML

GenAI knowledge

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Azure AI Search

Pinecone

Qdrant

Weaviate

Milvus

FAISS

Elasticsearch

OpenAI/Azure OpenAI

AWS Bedrock

Vertex AI

Job description

Avensys Consulting is seeking a Senior AI Knowledge Engineer to design and deploy enterprise GenAI knowledge systems, including RAG pipelines, document ingestion and embeddings. You will build production-ready AI services and integrate with enterprise applications.

The role requires deep AI/ML expertise, hands-on work with LangChain, vector databases and cloud platforms (Azure/AWS/GCP). Collaboration on governance and scalable AI delivery is essential.