Hyperautomation and AI Solutions Architecture

• Degree in Computer Engineering, Telecommunications, or equivalent technical discipline, or equivalent practical experience.
• 5 years of experience in cloud architecture, systems integration, automation, or technology platforms.
• Experience in complex technology projects in corporate environments.

• Extensive knowledge of cloud architectures and mastery of cloud services and cognitive services (especially in Azure and Google).
• Analytical capacity, global vision, and a structured mindset for executing complex projects.
• Communication skills and the ability to engage with different work teams and management.

• Immersing you in innovative and challenging projects.
• Boosting your professional development through continuous training adapted to your needs and motivations.
• We are committed to the balance between professional and personal life. At Telefónica España we promote flexibility, positioning ourselves as a benchmark in new ways of working, schedules, working hours and work-life balance measures: you will be able to enjoy a hybrid work model.
• We offer you a permanent contract and a very attractive compensation package.
• Life insurance, pension plan, and private medical insurance.
• Inviting you to participate in our volunteering program.

WHAT ARE WE LOOKING FOR?

People with a strong desire to give their all and make a difference. Passionate about innovation and cutting-edge technologies.

With this opportunity, you will be able to delve into the exciting technological universe and be part of the change: a more connected, more human world, full of stories that transform lives.

WE WANT PEOPLE LIKE YOU…

Your challenge will be to technically lead the design, implementation, and evolution of the hyperautomation and AI platform architecture, ensuring its effective integration with corporate systems, its alignment with the company's cloud environments under criteria of scalability, security, and operational efficiency.

Challenge 1: Design and evolution of cloud architectures for AI solutions:

• Design and ensure the technical engineering of cloud architectures that support AI, data, and automation services.
• Define the necessary infrastructure (compute, storage, networks, containers, AI Gateway, load balancers) for corporate AI solutions.
• Ensure the scalability, resilience, and security of environments deployed in public or hybrid clouds.
• Collaborate on the design of distributed, microservices-oriented architectures for the efficient consumption of AI models and APIs.
• Evaluate the technical and economic impact of new cloud solutions applied to AI and automation.
• Define and govern the use of key cloud services (APIM, Functions, Vertex AI, AKS, Service Bus, Storage, OpenAI) as the foundation of the architecture.

Challenge 2: Integration and deployment of AI and automation services:

• Design the integration of cognitive services and AI APIs (Azure OpenAI, Vertex AI, etc.) with the organization's internal systems.
• Define the authentication, security, and access control mechanisms for these services, ensuring regulatory and technical compliance.
• Ensure proper interoperability between data platforms, automation (RPA, Power Platform, Service Bus), and AI services.
• Coordinate the deployment of new AI solutions within the corporate ecosystem, optimizing performance and availability.
• Oversee the use of test and production environments in AI service deployments, ensuring traceability and reversibility.
• Design decoupled integrations based on APIs and events (APIM, Service Bus).

Challenge 3: Design and evolution of the AI agent platform:

• Design and evolve the agent platform based on Microsoft Azure capabilities (Azure OpenAI, Foundry) and Google Cloud Platform (Vertex AI), ensuring coherence and complementarity between both environments.
• Define design patterns for agents: multi-agent orchestration, use of tools (APIs/MCPs), memory and context management.
• Design the exposure layer for agentic capabilities through APIs, ensuring security, access control, and governance.
• Establish agent governance mechanisms: prompt versioning, change control, auditing, and decision traceability.
• Define the integration of agents with the corporate ecosystem (APIs, events, data, automation), avoiding unnecessary coupling and dependencies.
• Define best practices to ensure security, isolation, and responsible use of models and tools within agents.
• Ensure agent observability: monitoring of executions, cost per interaction, latencies, and response quality.

Challenge 4: Infrastructure and observability of Hyperautomation and AI solutions:

• Configure and maintain the infrastructure required for the execution of AI services and agents (clusters, VMs, containers, serverless).
• Implement observability tools (monitoring, logging, metrics, and alerts) that enable real-time supervision.
• Integrate observability with corporate tools such as Application Insights / Log Analytics.
• Optimize cloud resource consumption and costs through automation and dynamic scaling policies.
• Ensure operational security and data protection in AI solution execution environments.

Challenge 5: Technical collaboration and project support:

• Support development and business teams in the technical definition of solutions that incorporate AI.
• Translate functional business requirements into technical designs aligned with the corporate architecture.
• Provide technical support in service integration and ensure compatibility with the organization's cloud ecosystem.
• Coordinate technical reviews and validations prior to production deployment.
• Coordinate with the various technology integrators to ensure technical alignment, delivery quality, and coherence with the defined architecture.

Challenge 6: Innovation and technological evolution of the hyperautomation and AI ecosystem:

• Analyze market developments in hyperautomation, AI, and cloud services to identify opportunities for technological improvement.
• Evaluate new architectures and tools related to agents, MLOps, cognitive APIs, and orchestration frameworks.
• Propose improvements in operational efficiency and cost reduction through the adoption of emerging technologies.
• Define technology roadmaps and evolution plans for the organization's AI and automation platform.
• Participate in the technical validation of vendors and strategic solutions in the AI and cloud domain.

DO YOU IDENTIFY WITH THIS? IT'S TIME TO MAKE THE LEAP!

WORK LOCATION: Nationwide, preferably Madrid.

Permanent