Senior AI Solutions Architect

hace 4 semanas


Madrid, Madrid, España Pearson A tiempo completo

About the Role:

We are seeking a talented Senior AI Solutions Architect to join our English Language Learning division at Pearson. As a key member of our team, you will be responsible for designing and implementing cutting-edge artificial intelligence solutions that enhance the learning experience.

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.

Requirements:

  • System architecture design and modelling
  • 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 modelling 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

Pearson's Benefits:

  • 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

Flexible working:

Pearson is committed to hybrid working practices and has adopted flexible remote and virtual working. Where possible our employees can choose to manage their attendance to the office more flexibly.

How to apply:

Thank you for your interest in applying for a role at Pearson. Please submit an updated CV and cover letter (optional) in English. If you have any additional questions or require further information, please do not hesitate to reach out to us. We look forward to receiving your application - Pearson Recruitment



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