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hace 2 meses
We are seeking a highly skilled Senior AI Solutions Architect to join our team at Pearson. As a key member of our English Language Learning division, you will play a critical role in designing and implementing cutting-edge artificial intelligence solutions that enhance the learning experience.
Key Responsibilities- Collaborate with cross-functional teams to define requirements and prioritize AI initiatives.
- Define the technical architecture and infrastructure required for AI-driven applications and platforms.
- Design and develop scalable AI models, algorithms, and systems that support personalized learning, adaptive assessments, and intelligent tutoring systems.
- Provide technical leadership and guidance to development teams in the implementation of AI algorithms and systems.
- Mitigate risks by identifying potential challenges and proposing solutions or alternative approaches.
- Facilitate effective communication and collaboration among cross-functional teams, including business stakeholders, developers, testers, and infrastructure teams.
- Conduct system assessments and performance reviews to identify areas for improvement and optimization.
- Stay up to date with the latest advancements in AI technologies, frameworks, and tools.
- Contribute to the development and maintenance of architectural frameworks, guidelines, and standards within the organization.
- Drive innovation by identifying opportunities to leverage AI and machine learning techniques to improve learning outcomes.
- Ensure compliance with security, privacy, and regulatory requirements in the design and implementation of solutions.
- Collaborate with project managers to define project scope, timelines, and deliverables, and provide technical input for project planning and estimation.
- System architecture design and modeling.
- Proficiency in one or more programming languages commonly used in AI development, such as Python, R, and Java.
- Proficiency in AI and ML concepts, algorithms, and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras.
- Application of AI to support adaptive learning, personalized feedback, intelligent tutoring, and assessment in alignment with pedagogical practices.
- Strong knowledge of AI techniques, including machine learning, natural language processing, computer vision, and recommendation systems.
- Strong understanding of generative & conversational AI and associated concepts, such as input safeguarding, topic rails, scenario validation, safety verification.
- Solid understanding of data engineering principles, data pipelines, and data preprocessing techniques.
- Database management systems (MySQL, SQL Server, MongoDB), Data modeling and database design.
- Cloud computing platforms and services (AWS, Azure, GCP).
- Integration technologies: ESB, message queues, API gateways.
- Security principles and best practices, including authentication, authorization, encryption.
- DevOps practices and tools (CI/CD, version control, automated testing).
- Performance optimization techniques, load balancing, scalability, and distributed system design principles.
- Microservices architecture and design principles.
- Understanding of software development lifecycle (SDLC) and Agile methodologies.
- Experience with security frameworks and technologies.
- Understanding of network protocols (TCP/IP, HTTP, REST).
- Knowledge of data integration techniques and protocols (SOAP, REST, XML, JSON).
- Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
- Understanding of virtualization, storage, and networking.
- 24 Days annual leave (increasing by 1 day with every 2 years of continuous service up to 30 days).
- Private medical insurance.
- Life insurance Policy.
- Food & Transport Allowance.
- Work-Life Balance Benefits.
- Family Benefits.
- Complementary Benefits.
- Development and Training Benefits.
- Access to Pearson+: Pearson's digital library.
- Discounts on books.
- Development and training: a wide access to internal learning platforms and development plan.
