Knowledge: 

• ​​Strong knowledge of software engineering techniques and development processes and tools, for example, IDEs, SCCS, Algorithms and Data Structures, Automated testing and computer system and cloud operations​ 

• Advanced proficiency with Python; working familiarity with ML frameworks such as TensorFlow or PyTorch 

• Strong knowledge of current AI/ML technologies and their applications 

• Team leadership and team dynamics  

• Strong knowledge of agentic AI engineering — designing, building and orchestrating AI agents, including agent frameworks, tool/function calling, multi-agent workflows, MCP (Model Context Protocol) servers and reusable agent skills 

• Familiarity with modern AI-assisted engineering tools (e.g. Claude Code, Codex, Kiro, agent loops and automations) 

• Understanding of designing and operating agent platforms on cloud (AWS preferrably), including containerisation (Docker/Kubernetes), MLOps/LLMOps and CI/CD 

• Understanding of responsible AI, AI safety and governance — guardrails, security, data privacy, and evaluation/testing of LLM and agent applications (e.g. A/B and back-to-back testing, ModelOps/LLMOps) 

Experience: 

• ​​Minimum of 2 years' experience in a relevant AI, machine learning or software engineering role covering solution development, implementation and deployment, with extensive commercial development in Python (or similar languages)​ 

• Demonstrated experience with cloud technology (e.g. AWS, Azure or similar) and in analysing and organising structured and unstructured data 

• Strong communication and stakeholder management skills 

• Extensive experience in analysing and developing software applications to deliver business solutions 

• Demonstrated experience building AI agents, MCP (Model Context Protocol) servers and reusable skills for specific business use cases, using modern AI-assisted development tools (e.g. Claude Code, Codex, Kiro, agent loops and automations) 

• Experience designing and building agent / AI platforms on cloud, delivering scalability, cost efficiency, safety, security and the evaluation/testing of agent and LLM applications 

• Demonstrated experience in applied AI engineering, machine learning and data science, including working with language models, RAG, vector databases and knowledge graphs 

• Experience working in and leading software engineering teams across a full-stack development environment 

• Experience in the electricity industry desirable