Senior AI

Overview

As a Senior AI/ML Engineer at our fast-growing online learning platform, you lead AI strategy and architect scalable AI services that power personalised learner experiences. You work across product, engineering, data, and learning teams to deliver innovative, production-ready AI features with a strong emphasis on quality and responsible AI. You mentor engineers, set engineering standards, and help shape the future of our technology to impact millions of learners. This hybrid role blends hands-on delivery with technical leadership in a mission-driven environment.

Responsibilities

• Define and deliver the technical vision for AI across the learning platform
• Architect and build scalable AI services using LLMs, ML, and cloud technologies
• Develop intelligent learning experiences (personalised journeys, AI tutors, content generation, assessments, recommendations, learner support)
• Build production-ready AI systems prioritising quality, reliability, security, and performance
• Collaborate with Product, Learning Design, Data Science, and Engineering to deliver customer-focused solutions
• Evaluate new AI technologies to improve learner engagement and outcomes
• Establish engineering standards, AI governance, and best practices across the organisation
• Mentor senior engineers and grow a high-performing AI engineering capability

Key requirements

• Extensive experience building and deploying AI or ML products in production
• Expert-level Python software engineering
• Strong experience with LLMs, RAG, AI agents, prompt engineering, and model evaluation
• Cloud-native development on Azure, AWS, or Google Cloud
• Solid understanding of MLOps, CI/CD, Kubernetes, containerisation, and scalable architectures
• Experience integrating AI into customer-facing products
• Excellent communication to influence technical and non-technical stakeholders
• Proven experience leading technical teams and mentoring engineers

• Excellent communication and Stakeholder influence
• Leadership and mentoring abilities
• Collaborative cross-functional working
• Python
• LLMs
• Retrieval-Augmented Generation (RAG)

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