Role Summary
We are partnering with a leading research and innovation organisation 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#, Fast
- API or similar, preferably in manufacturing domain with MES/ERP systems Has experience with the following tech stack: Agent frameworks (e.g., Lang
- Chain, Lang
- Graph) 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
