• Lead the design and implementation of scalable, high-performance software systems for Generative AI applications. • Collaborate with data science team and other engineering teams to translate cutting-edge algorithms and models, including Large Language Models (LLMs), into production-ready software solutions. • Optimise algorithms and workflows to improve performance, efficiency, and scalability, leveraging LLMs where applicable. • Conduct code reviews, provide technical guidance, and mentor other engineers to ensure code quality and best practices. • Construct and maintain data pipelines, engage in data upkeep, and contribute to the training and automation of all aspects of the lifecycle of LLMs. • Stay updated on the latest advancements in AI research and technology, including developments in LLMs, and apply them to enhance our Generative AI engineering capabilities. • Contribute to architectural decisions and technical strategy to drive innovation and maintain competitive advantage, incorporating LLMs where suitable. • Research, develop, and implement cybersecurity measures to safeguard our Generative AI systems against potential threats, including those specific to Generative AI. • Collaborate with engineering team to assess risks, implement security best practices, and ensure compliance with industry standards and regulations, particularly in the context of LLM usage. • Own your work with autonomy, end to end: develop, test, deploy and monitor your changes. • Thrive in an environment that highly values trust.

• Collaborate with development teams to understand requirements and provide technical guidance throughout the project development cycle. • Design and implement cloud-native solutions on Azure, ensuring scalability, performance, security, and maintainability. • Develop and enforce standards, guidelines, and best practices for software development. • Identify risks and propose technical solutions to mitigate them. • Conduct code reviews and ensure adherence to best software development practices. • Investigate and evaluate new technologies, tools, and frameworks relevant to software development on Azure. • Act as a hands-on technical reference and mentor for less senior developers, promoting knowledge sharing and best practices.

• Lead feature development end to end across React-based interfaces and Node.js / Express backend services • Own the frontend architecture: component design, state management, performance, accessibility, and the overall feel of the product • Build and maintain REST and GraphQL APIs, handle data modelling, and keep backend services clean, well-tested, and predictable • Take applications from local environments to production. CI/CD pipelines, environment setup, monitoring, alerting, and incident response sit with you • Review code, mentor the junior engineer on the squad, and set technical direction for the team • Work directly with product stakeholders. Translate ambiguous requirements into shipped work without long handoffs • Use AI-assisted development tools (Cursor, Claude Code, GitHub Copilot) as a core part of your daily workflow, not as an afterthought

• Own and build production systems end to end - backend, frontend, data layer, and infrastructure. • Design and implement AI-powered workflows using LLMs, retrieval systems, and automation pipelines. • Build and maintain CI/CD pipelines, cloud infrastructure (AWS), and deployment automation. • Set up monitoring, logging, and alerting so the systems you build stay healthy in production. • Integrate with third-party APIs and enterprise systems (CRMs, messaging platforms, identity providers). • Translate ambiguous requirements into shipped product - you don't wait for a perfect spec.