Senior Cognitive Architecture Expert

Vacancy: Application Architecture ROLE

Organizational Levels: Operations and Technology > Technology > Architecture > Core Architecture > Cognitive Architecture

We are currently looking to hire an Architect / Architect Specialising in Artificial Intelligence Models in Sabadell to join the bank's cognitive architecture team.

Let's talk about the project...

Integrated within the Artificial Intelligence and Cognitive Systems Architecture Directorate, the professional will act as a technological reference in the field of Artificial Intelligence models and the organization's advanced cognitive capabilities.

The position has a strong component of technological specialization and capability evolution, contributing to defining how AI models should be used within the bank, how to integrate them into the corporate ecosystem, and how to evolve them in alignment with the technological strategy and business needs.

The selected person will help define reference architectures for capabilities based on Artificial Intelligence, participating in both technological evolution and the implementation of enterprise solutions supported by pre-trained models, specialized models, fine-tuned models, and proprietary models.

They will work cross-functionally with solution architects, engineering teams, business areas, data teams, technological platforms, and specialized providers, providing technological vision, market knowledge, and expertise in Artificial Intelligence models, frameworks, architectures, and infrastructures.

The main focus of the position will be oriented toward the use of AI capabilities on unstructured information, including documents, images, audio, video, natural language, and corporate knowledge, facilitating its exploitation within enterprise processes and applications.

Mission

Act as a technological reference for model-based Artificial Intelligence capabilities, contributing to defining their technological strategy, evolution, adoption, and utilization model within the bank.

Their mission will be to drive the efficient use of AI capabilities through the correct selection, training, specialization, deployment, orchestration, and integration of Artificial Intelligence models, ensuring that they generate business value through scalable, secure, governed solutions aligned with corporate standards.

The position will contribute to the adoption of advanced AI capabilities for unstructured information processing, intelligent process automation, knowledge extraction, and the incorporation of cognitive models within the organization's technological architecture.

Strategy and Architecture

Designs and provides a global vision of the company's IT, creating a single global architecture of applications and technological systems upon which Business services rely. Simplifies IT governance and management by achieving demanded service levels, optimizing costs, and maximizing efficiency.

• Define reference architectures for the development, training, deployment, consumption, and operation of Artificial Intelligence models.
• Design reference frameworks for capabilities based on Generative AI, Predictive AI, Multimodal AI, and Document Intelligence.
• Establish standards for integration, security, observability, traceability, and governance.
• Evaluate market platforms, frameworks, architectures, and technologies.
• Contribute to the definition of the bank's Artificial Intelligence technological roadmap.
• Define industrialization and scaling patterns for AI model-based capabilities.

Technological specialization and market vision

• Maintain deep knowledge of the predominant models, architectures, and technologies in the market.
• Understand the evolution of major manufacturers, platforms, and model marketplaces.
• Analyze technological trends and emerging capabilities.
• Evaluate the applicability of new technologies to the bank's context.
• Act as a point of reference for technological issues related to Artificial Intelligence models.
• Identify opportunities for incorporating new models and capabilities into the corporate technological ecosystem.

Artificial Intelligence Models

• Define utilization patterns for foundational, specialized, and proprietary models.
• Advise on model selection according to functional, operational, regulatory, and cost requirements.
• Identify opportunities for the use of pre-trained, fine-tuned, or internally developed models.
• Define strategies for training, fine-tuning, specialization, and adaptation of models.
• Design multi-model architectures and coordination patterns between models.
• Continuously evaluate the performance, quality, and suitability of the models used.

Unstructured information processing

• Define patterns for the processing and exploitation of unstructured information.
• Design architectures for Document Intelligence capabilities.
• Facilitate knowledge extraction from documents, images, audio, and video.
• Drive the use of AI for document classification, entity extraction, and semantic analysis.
• Define mechanisms for incorporating extracted knowledge into corporate processes and applications.
• Contribute to the construction of corporate platforms based on knowledge and cognitive capabilities.

Orchestration and coordination of AI capabilities

• Define orchestration patterns for distributed AI capabilities.
• Design architectures capable of coordinating multiple Artificial Intelligence models and services within complex processes.
• Establish collaboration mechanisms between specialized models.
• Define batch, near real-time, real-time, and on-demand execution strategies.
• Design architectures for assisted and unassisted scenarios.
• Participate in the definition of intelligent workflow execution platforms.
• Drive the use of orchestration frameworks and AI-based process coordination.
• Design resilience, traceability, and recovery mechanisms in distributed Artificial Intelligence flows.
• Define event-based integration models and decoupled architectures.

Architecture and project support

• Advise solution architects on initiatives that incorporate Artificial Intelligence capabilities.
• Collaborate with technical units in the definition of complex solutions.
• Participate in technical reviews of strategic projects.
• Facilitate the reuse of common components, services, and patterns.
• Define recommendations for different corporate use scenarios.
• Act as a technical reference in the definition of AI-based architectures.

Integration into the technological ecosystem

• Define integration patterns for AI capabilities with business applications and processes.
• Design architectures for synchronous, asynchronous, batch, and real-time consumption.
• Establish integration models through APIs, events, and microservices.
• Guarantee interoperability with corporate platforms.
• Facilitate the integration of models within distributed and cloud architectures.
• Define best practices for the consumption of AI capabilities from enterprise applications.

Infrastructure, deployment, and scalability

• Define architectures for the efficient deployment of Artificial Intelligence models.
• Participate in the definition of GPU infrastructures for training and inference.
• Evaluate hardware acceleration technologies for AI workloads.
• Define horizontal and vertical scalability patterns.
• Establish recommendations for the optimization of inference costs.
• Design hybrid and multi-cloud architectures for cognitive capabilities.
• Define operating models for large-scale AI capabilities.

Governance and model lifecycle

• Define standards for the comprehensive management of the model lifecycle.
• Participate in the definition of validation and certification processes.
• Establish criteria for continuous monitoring and evaluation.
• Define traceability, explainability, and audit models.
• Collaborate in the implementation of AI Governance capabilities.
• Contribute to the adoption of MLOps and ModelOps practices.

Relationship with providers and the technological ecosystem

• Act as a technological interlocutor with manufacturers and specialized partners.
• Participate in technological evaluations and roadmap sessions.
• Analyze the capabilities offered by platforms, cloud services, and manufacturers.
• Evaluate risks, dependencies, and adoption opportunities.
• Contribute to strategic technological decision-making.
• Maintain an updated view of the enterprise Artificial Intelligence ecosystem.

Driving transformation and adoption

• Promote the adoption of advanced Artificial Intelligence capabilities within the organization.
• Share knowledge and best practices.
• Contribute to the definition of corporate standards.
• Support different teams in incorporating new AI capabilities.
• Act as an internal reference regarding Artificial Intelligence models and platforms.

119 Data architecture

80 Log detection and correlation technologies

109 Observability (ElasticSearch Kafka grafana..)

115 Infrastructure solutions knowledge

118 Application architecture

203 Cloud Architectures

112 Middleware (web server, application servers..)

116 Cross & insurance channel platform architecture

201 Mainframe Architecture

202 Middleware and application server architecture

117 Corporate banking services platform architecture

57 Project Management