Role Summary

We are partnering with a leading research and innovation organization to hire a Junior/Senior Research Engineer to build Agentic Intelligence systems for planning, scheduling, and inventory optimization in manufacturing and operations environment. In this role, you will work on agent-based AI systems, combining Large Language Model (LLM), optimization techniques, and real-world data to create scalable, production-ready solutions.

Key Responsibilities

• Build and improve multi-agent systems for planning, scheduling, and inventory tasks
• Combine LLMs with optimization methods to solve complex real-world problems
• Design and extend semantic reasoning layers (intents, constraints, domain logic)
• Model operational data using knowledge graphs + vector search
• Develop event-driven backend services and APIs integrated with enterprise systems
• Improve agent orchestration, tool integration, and workflows
• Set up evaluation, monitoring, and guardrails (cost, latency, reliability)
• Deploy and run services using Docker, Kubernetes, and CI/CD pipelines
• Collaborate with AI/ML engineers to bring research into production
• Work with end users (planners/operators) to ensure practical, usable solutions
• Leverage AI coding tools to improve development speed and quality

Our Ideal Candidate

• Has a Bachelor's Degree in Computer Engineering, Software Engineering, or related field.
• Has at least 5 years of experience building production backend systems using Python, C#, FastAPI or similar, preferably in manufacturing domain with MES/ERP systems
• Has experience with the following tech stack:
• Agent frameworks (e.g., LangChain, LangGraph)RAG systems (retrieval, chunking, reranking, evaluation)Vector databases (Pinecone, Qdrant, etc.)Event-driven systems (Kafka or similar)
• Has strong knowledge of cloud (AWS/Azure/GCP), Docker, Kubernetes, CI/CD
• Has excellent problem-solving, troubleshooting, and analytical skills
• Has effective communication and collaboration skills

UEN:202329526G

EA Licence: 23S2061