AI Agent Engineer

Key Responsibilities 1. Design, develop and maintain AI Agent applications powered by Large Language Models (LLMs), including intelligent Q&A, task planning, tool calling, workflow orchestration, multi-agent collaboration and long-term memory. 2. Design technical solutions and build production-ready AI applications using leading LLMs and Agent frameworks, covering solution architecture, prototyping, implementation, testing, deployment and continuous optimisation. 3. Develop and optimise key AI capabilities including: · Prompt Engineering · Retrieval-Augmented Generation (RAG) · Enterprise Knowledge Base · Function Calling · Model Context Protocol (MCP) integrations 4. Integrate LLM capabilities with existing enterprise applications, business systems, databases and third-party APIs to automate and enhance business workflows. 5. Establish evaluation and monitoring mechanisms for AI applications, continuously improving: · task completion rate · response accuracy · system reliability · latency · model inference cost 6. Participate in AI product planning, system architecture design, API design, technical reviews and end-to-end project delivery. 7. Keep up to date with the latest developments in LLMs, AI Agents and related technologies, conducting technical research, proof-of-concepts and production implementation. 8. Collaborate closely with Product Managers, AI Scientists, Backend Engineers and business stakeholders to independently deliver core product features. Requirements Education · Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, Data Science or a related discipline. Experience · Minimum 5 years of software engineering or backend development experience with strong software engineering fundamentals and coding best practices. · Strong proficiency in Python. · Solid understanding of: o data structures o object-oriented design o design patterns o concurrent programming o RESTful API development o exception handling · Experience developing backend services using FastAPI, Flask, Django or other modern Python frameworks. AI / LLM Experience · Hands-on experience building LLM-powered applications using one or more of the following: o OpenAI o Claude o Gemini o Qwen o DeepSeek o or equivalent commercial/open-source models. · Strong understanding of: o AI Agents o Prompt Engineering o Retrieval-Augmented Generation (RAG) o Function Calling o Model Context Protocol (MCP) o Workflow orchestration · Experience with one or more AI frameworks/platforms, such as: o LangChain o LangGraph o LlamaIndex o AutoGen o Dify o FastGPT o Coze Engineering Skills · Experience with Git, Docker, Linux and CI/CD pipelines. · Familiarity with production deployment, monitoring and troubleshooting. · Experience working with relational, vector or search databases, including one or more of: o PostgreSQL o MySQL o Redis o Milvus o Elasticsearch o FAISS Preferred Qualifications Candidates with one or more of the following will be highly regarded: · Production experience building AI Agents, enterprise knowledge bases, intelligent assistants or multi-agent systems. · Experience in LLM fine-tuning, embedding models, reranking, model evaluation, inference optimisation or model serving. · Experience with microservices, distributed systems, cloud-native architecture and high-concurrency backend systems. · Industry experience in Energy Storage (BESS), Power & Energy, Industrial IoT, Smart Energy or Enterprise Digitalisation. Soft Skills · Strong analytical thinking and problem-solving skills. · Ability to independently own and deliver end-to-end technical modules. · Excellent communication and cross-functional collaboration skills. · Ability to read and understand English technical documentation.