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#, 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
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