AI Engineer

• Work-life balance measures and flexible hours.• Ongoing training and certifications.• Hybrid remote work model.• Attractive social benefits package.• Excellent dynamic and multidisciplinary work environment.• Volunteering programs.

The AI & Big Data business unit at Telefonica Tech helps its clients in their digital transformation process by unifying Artificial Intelligence, Big Data, IoT, and Blockchain capabilities. This team's mission is to help organizations increase their results through a global offering of products and services such as strategic consulting, infrastructure deployment, the development and industrialization of analytical models, and training on new technologies, among others. In this way, we need motivated people, with real knowledge related to the subject, and a desire to continue learning new technologies.

The Data Science / AI Engineering team is responsible for designing and deploying advanced Artificial Intelligence solutions, with a growing focus on Generative AI, Large Language Models (LLMs), and intelligent agent systems.

We work with organizations from multiple sectors (public administration, industry, banking, healthcare, sports, etc.) and use the major cloud hyperscalers (Microsoft Azure, AWS, Google Cloud, among others), applying agile methodologies and engineering best practices to bring our solutions into production.

We are looking for people with a highly technical profile and an engineering mindset, an interest in Generative AI and advanced AI systems, and the motivation to continue learning and evolving in an environment of continuous innovation.

As an Artificial Intelligence Engineer, you will actively participate in the design, development, optimization, and deployment of AI solutions, with a special focus on their industrialization and scaling.

Your role will be oriented towards building end-to-end AI systems, combining Machine Learning and Deep Learning models (including LLMs) with robust software architectures, automated pipelines, and MLOps/LLMOps practices.

Some of the day-to-day activities may include:

Participating in the definition of technical architectures for AI solutions, aligned with business requirements and corporate standards.

Designing, training, evaluating, and optimizing Machine Learning and Deep Learning models, including Generative AI models.

Develop applications based on LLMs, such as RAG systems, intelligent agents, and specialized copilots.

Adapt and optimize LLMs through fine-tuning, adapters (LoRA, PEFT), and inference optimization techniques.

Integrate structured and unstructured knowledge sources (databases, search engines, documents, APIs).

Build and expose APIs and services that integrate LLMs into production environments.

Design and implement MLOps/LLMOps practices: deployment, monitoring, observability, cost control, and governance.

Evaluating new trends, models, and frameworks for AI and agents, and bringing them into production when they add value.

Guarantee aspects of security, privacy, compliance, and AI responsibility in LLM-based systems.

Generating documentation and transferring knowledge to the various stakeholders.

Providing technical training on topics within their domain.

Staying updated on technical tools and trends.

To perform the role, the skills that would best fit the team and the project would be:

Teamwork and a collaborative attitude.

Engineering mindset and production orientation.

Ability to design complex systems in a structured manner.

Clear communication with technical and business profiles.

Collaborative spirit

Strong learning ability

Proactivity, autonomy, and continuous learning.

Experience with agile methodologies (such as Scrum)

Ability to document and explain technical decisions.