Senior GenAI Applications Engineer — Production LLMs & RAG

D L RESOURCES PTE LTD; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Bank Sector Client Located In Singapore is seeking a Senior GenAI Application Engineer to design, build and deliver production-grade GenAI/LLM applications for enterprise environments.

You will work across LLM application development, RAG, agentic AI, LangGraph/LangChain orchestration, backend services and production deployment. Strong backend fundamentals and experience moving GenAI apps to production are essential.

Qualifications

• 6+ years of software engineering experience
• Strong backend development experience using Python, Java or similar languages
• Strong understanding of REST APIs / API development
• Backend services, distributed systems and enterprise integration
• Production-grade code quality and maintainability
• Experience taking GenAI apps from POC to production

Responsibilities

• Design, develop and deploy production-grade GenAI/LLM applications for enterprise users
• Build AI Agent workflows using LangGraph/LangChain or similar orchestration frameworks
• Develop RAG solutions including retrieval workflows and prompt orchestration
• Integrate LLM applications with enterprise systems, REST APIs and databases
• Support model integration and LLM inference/model-serving architectures
• Deploy GenAI apps in containerized environments (Kubernetes/OpenShift)

Skills

GenAI applications

Python/Java backend

REST APIs

LangGraph

LangChain

RAG

AI Agents/Agent workflows

Kubernetes/OpenShift

LLM observability

Tools

LangGraph

LangChain

Kubernetes

OpenShift

vLLM

Elasticsearch

Redis

Job description

Bank Sector Client Located In Singapore is seeking a Senior GenAI Application Engineer to design, build and deliver production-grade GenAI/LLM applications for enterprise environments.

You will work across LLM application development, RAG, agentic AI, LangGraph/LangChain orchestration, backend services and production deployment. Strong backend fundamentals and experience moving GenAI apps to production are essential.