Junior AI Engineer (LLM/ Generative AI)
- Build, iterate, andmaintain LLM-powered applications — including chatbots, document processingpipelines, predictive analytics interfaces, and intelligent search systems
- Design and optimise RAG(Retrieval Augmented Generation) pipelines: chunking strategies, embeddingmodel selection, retrieval tuning, and context window management
- Develop and refine promptengineering frameworks — maintaining prompt libraries, evaluating promptperformance, and implementing prompt versioning
- Fine-tune open-weightmodels (Llama, Mistral) on YCH-specific logistics data to improve domainaccuracy and reduce inference costs
- Integrate LLM capabilitiesinto YCH's legacy Java application APIs — building clean abstraction layersthat allow AI features without full system rewrites
- Implement LLM evaluationpipelines using automated scoring (faithfulness, relevance, hallucination rate)and human evaluation frameworks
- Collaborate with BusinessAnalysts to translate new use case specifications into production AI features
- Contribute to internal AIdocumentation, prompt libraries, and reusable component libraries
Job Requirements:
- 1+ years working or projectexperience on LLM or AI application development
- User InterfaceEngineering: Build dynamic, real-time UI components using React and Next.js tohandle AI streaming responses, multi-step agent status indicators, and markdownformatting.
- AI BackendOrchestration: Design scalable backend API routes and background event queuesusing Node.js and TypeScript.
- Hands-on experience withLLM frameworks: LangChain, LangGraph, LlamaIndex, or equivalent
- Understanding of RAGarchitecture, vector databases, and embedding models
- Experience consuming LLMAPIs (OpenAI, Azure OpenAI, Vercel AI, Anthropic Claude)
- Solid software engineeringfundamentals: version control, testing, code review, documentation
- Java development background— ideal for reskilled internal candidates with logistics context
- Fine-tuning experience withopen-weight models (Llama, Mistral, Phi)
- Knowledge of logisticsdomain: freight documents, customs, route planning is favoured.
- Experience with agentic AIframeworks (AutoGen, CrewAI, LangGraph)