Senior AI Solution Architect

<p>Role:<strong>           Senior AI Solution Architect</strong></p> <p>Company:<strong>   Pearson</strong></p> <p>Division:<strong>      English Language Learning </strong></p> <p>Location:<strong>     Spain - Madrid (remote or hybrid*)</strong></p> <p> </p> <p>*If you live in Madrid, you will be able to enjoy our brand-new office because we a have a remote / hybrid working model policy in place!</p> <p> </p> <p><strong>About Pearson:</strong></p> <p>Our purpose: At Pearson we ‘add life to a lifetime of learning’ so everyone can realise the life they imagine. We do this by creating vibrant and enriching learning experiences designed for real-life impact. Pearson was founded in 1844 and has been built on our ability to grow with and adapt to a constantly evolving market. Our 20,000+ employees are dedicated to creating the high-quality, digital-first, accessible and sustainable resources for lifelong learning.</p> <p> </p> <p><strong>About English Language Learning:</strong></p> <p>In the English Language Learning (ELL) business unit, we aspire to become the world's leading destination to learn and improve English language skills. Our main focus is on committed learners from around the world, who are motivated by outcomes because they want to reach their full potential through learning English.</p> <p> </p> <p><strong>About the Role:</strong></p> <p>Do you want to be part of the biggest digital transformation in the EdTech and help people around the world to learn languages and realise their dreams? The English Language Learning (ELL) division of Pearson is looking for a talented and motivated professional to join our growing team of architects as a Solution Architect. Reporting to the Chief Architect you will be responsible for designing and implementing cutting-edge artificial intelligence solutions that enhance the learning experience.</p> <p> </p> <p><strong>Job Description:</strong></p> <ul> <li>Collaborate with cross-functional teams including product managers, engineers, data scientists, and subject matter experts to define requirements and prioritize AI initiatives.</li> <li>Define the technical architecture and infrastructure required for AI-driven applications and platforms.</li> <li>Design and develop scalable AI models, algorithms, and systems that support personalized learning, adaptive assessments, and intelligent tutoring systems. </li> <li>Provide technical leadership and guidance to development teams in the implementation of AI algorithms and systems.</li> <li>Mitigate risks by identifying potential challenges and proposing solutions or alternative approaches. </li> <li>Facilitate effective communication and collaboration among cross-functional teams, including business stakeholders, developers, testers, and infrastructure teams. </li> <li>Conduct system assessments and performance reviews to identify areas for improvement and optimization. </li> <li>Stay up to date with the latest advancements in AI technologies, frameworks, and tools.</li> <li>Contribute to the development and maintenance of architectural frameworks, guidelines, and standards within the organization. </li> <li>Drive innovation by identifying opportunities to leverage AI and machine learning techniques to improve learning outcomes.</li> <li>Ensure compliance with security, privacy, and regulatory requirements in the design and implementation of solutions. </li> <li>Collaborate with project managers to define project scope, timelines, and deliverables, and provide technical input for project planning and estimation </li> </ul> <p> </p> <p><strong>Qualifications &amp; Skills </strong></p> <ul> <li>System architecture design and modelling </li> <li>Proficiency in one or more programming languages commonly used in AI development, such as Python, R, and Java</li> <li>Proficiency in AI and ML concepts, algorithms, and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras</li> <li>Application of AI to support adaptive learning, personalized feedback, intelligent tutoring, and assessment in alignment with pedagogical practices</li> <li>Strong knowledge of AI techniques, including machine learning, natural language processing, computer vision, and recommendation systems</li> <li>Strong understanding of generative &amp; conversational AI and associated concepts, such as: input safeguarding, topic rails, scenario validation, safety verification</li> <li>Solid understanding of data engineering principles, data pipelines, and data preprocessing techniques</li> <li>Database management systems (MySQL, SQL Server, MongoDB), Data modelling and database design </li> <li>Cloud computing platforms and services (AWS, Azure, GCP) </li> <li>Integration technologies: ESB, message queues, API gateways </li> <li>Security principles and best practices, including authentication, authorization, encryption </li> <li>DevOps practices and tools (CI/CD, version control, automated testing) </li> <li>Performance optimization techniques, load balan