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.