Education

• Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience

Responsibilities

• Design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production
• Act as a hands-on technical leader, spending significant time designing, coding, reviewing, debugging, and improving production systems that support AI-powered products and services
• Design and build scalable backend services, application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale
• Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration
• Make key technical decisions while remaining accountable for practical implementation quality, including code maintainability, system performance, reliability, security, scalability, and cost efficiency
• Establish engineering best practices through hands-on contribution, code reviews, technical design reviews, automated testing, observability, monitoring, and operational excellence
• Champion machine learning operations practices including model lifecycle management, prompt versioning, automated evaluation, deployment pipelines, monitoring, and continuous improvement
• Partner with product managers, data scientists, machine learning engineers, engineering leaders, and business stakeholders to translate strategic priorities into robust, buildable technical solutions
• Build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development across multiple teams without creating unnecessary abstraction or complexity
• Evaluate emerging AI technologies through practical prototypes, proof-of-concept builds, and production-readiness assessments, then guide teams on implementation patterns and trade-offs
• Mentor engineers through practical technical coaching, pairing, code reviews, design feedback, documentation, and example-setting as a senior individual contributor

About The Team

• Our Digital Content and Innovation (DC&I) team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact.
• Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.