AI Principal Engineer

We're looking for an experienced Principal Engineer to play a key role in shaping and delivering AI-driven solutions that will serve the entire organization. This is a fast-paced, high-impact role, ideal for engineers who thrive in rapid iteration cycles and want to shape how applied AI delivers real business value across a global enterprise. As a member of the team, you'll drive the development of Agentic AI systems, leveraging best of breed LLMs, AI cloud services and frameworks. Your work will help scale AI adoption across the organisation, ensuring solutions are robust, reliable, explainable, and operationally sound. You should be highly proficient in Python and modern engineering practices, comfortable working across both backend and frontend environments, and experienced in translating traditional software engineering approaches into emerging AI assisted methods. Strong collaboration, evaluation driven thinking, and a product mindset are essential. If you're excited by the challenge of delivering Agentic AI solutions at scale and influencing how AI transforms an enterprise, we'd love to hear from you. The team The "AI and Innovation" team is part of the Global Technology division, operating as a centre of excellence for applied AI and agentic systems. We deliver AI enabled products, frameworks, and internal tools used across the business, helping teams adopt modern AI patterns safely, reliably, and efficiently. We work across the full lifecycle from experimentation to productionisation, using agile and DevOps practices. What you'll do • Design, develop, and deliver AI-enabled features and agent-driven workflows that solve real business challenges. • Build resilient production systems leveraging cloud-native AI services, agent frameworks, and LLM APIs (e.g., OpenAI, Anthropic). • Implement agent-based architectures encompassing reasoning loops, guardrails, observability, and operational controls. • Collaborate closely across teams to gather requirements and iterate quickly, employing agile and DevOps principles. • Champion quality and security with a "shift-left" testing mindset, ensuring compliance and reliability in AI solutions. • Monitor AI system behaviour post-deployment, clearly communicating limitations, risks, and performance. • Use AI-assisted coding tools to boost developer productivity and code quality within the team. • Engage in continuous improvement through code reviews, evaluation design, and metrics-driven iteration. The knowledge, experience and qualifications you need • Strong software engineering background, with Python first development experience. • Proven experience building production systems that integrate with LLM API services e.g. OpenAI API services. • Hands on experience with agentic or tool using AI systems, including orchestration, memory, and toolchains. • Experience designing and using evals to measure model quality, reliability, safety, and regression. • Comfort working with cloud managed AI services and modern agent frameworks. • Familiarity with RAG workflows, vector stores, embedding design, and latency/cost trade offs. • Experience thinking about (and engineering for) failure modes, guardrails, operational reliability, and user impact.