AI Engineer

Bell Integration Spain; Valencia; On-site; EUR 55,000 - 85,000; Full time

Job summary

Bell Integration Spain is seeking an AI Engineer in the IP Development team to embed AI across the software development lifecycle, driving practical, scalable AI enhancements in delivery, quality and user experience.

You will collaborate with Engineering Managers, the Principal Developer, Software Architect, and Product teams to embed AI into product development and platform operations, including RAG-based solutions and robust prompt design, while promoting safe and responsible AI practices.

Qualifications

• Experience with AI/ML technologies, especially LLMs and modern AI tooling.
• Hands-on experience building or integrating AI-enabled applications (e.g. RAG, AI-assisted workflows).
• Strong prompt design, evaluation, and techniques to improve output quality and consistency.
• Experience with APIs and integrating external services into applications.
• Knowledge of vector databases, embeddings, and information retrieval.
• Understanding of software development practices and how AI fits into the development lifecycle.
• Ability to collaborate effectively with engineering, product, and design teams.
• Strong problem-solving skills with a practical approach to experimentation and delivery.
• Comfortable with a fast-evolving space and changing tools.
• Strong communication skills to explain AI concepts clearly.
• Experience using AI-assisted development tools (e.g. Copilot, Claude Code).
• Hands-on software development experience (TypeScript, Python) is beneficial.

Responsibilities

• Identify and deliver practical AI use cases across the development lifecycle (e.g. planning, design, development, testing, and support)
• Design, build, and improve AI-enabled features within our platforms, including RAG-based solutions and LLM integrations
• Develop and refine prompts, workflows, and evaluation approaches to improve reliability, accuracy, and usefulness of AI outputs
• Work closely with Engineering and Architecture to ensure AI solutions are scalable, maintainable, and aligned with platform design
• Collaborate with Product teams to identify opportunities where AI can enhance user experience or unlock new capabilities
• Support the integration of AI services and tooling (e.g. model APIs, orchestration layers, vector stores) into existing systems
• Help define and evolve best practices for using AI within the team, including quality, security, and governance considerations
• Enable and upskill the wider team by sharing knowledge, running sessions, and supporting hands-on adoption of AI tools
• Evaluate emerging tools and technologies, balancing experimentation with practical implementation
• Contribute to improving team efficiency through the use of AI-assisted development tools and workflows
• Monitor and assess the effectiveness of AI implementations, iterating based on feedback and outcomes
• Where appropriate, support the safe and responsible use of AI, including data handling, prompt safety, and output validation

Skills

AI/ML experience

LLMs

API integration

Prompt design

Vector databases

Embeddings

TypeScript

Python

Development lifecycle

Collaboration

Copilot

Claude Code

Tools

Copilot

Claude Code

Job description

As an AI Engineer in the IP Development team, you will be responsible for driving the effective use of AI across our software development lifecycle. Your focus will be on identifying where AI can improve delivery, quality, and user experience, and turning those opportunities into practical, scalable solutions.

You will work closely with Engineering Managers, the Principal Developer, Software Architect, and Product teams to embed AI into both how we build products and how our platforms operate. This includes enhancing existing capabilities (e.g. retrieval-augmented generation), improving prompt design and reliability, and exploring new use cases that deliver real value.

You will also play a key role in enabling the wider team, helping developers, designers, and product teams adopt AI tools and approaches in a way that is effective, responsible, and aligned to our engineering standards.

Role Responsibilities

• Identify and deliver practical AI use cases across the development lifecycle (e.g. planning, design, development, testing, and support)
• Design, build, and improve AI-enabled features within our platforms, including RAG-based solutions and LLM integrations
• Develop and refine prompts, workflows, and evaluation approaches to improve reliability, accuracy, and usefulness of AI outputs
• Work closely with Engineering and Architecture to ensure AI solutions are scalable, maintainable, and aligned with platform design
• Collaborate with Product teams to identify opportunities where AI can enhance user experience or unlock new capabilities
• Support the integration of AI services and tooling (e.g. model APIs, orchestration layers, vector stores) into existing systems
• Help define and evolve best practices for using AI within the team, including quality, security, and governance considerations
• Enable and upskill the wider team by sharing knowledge, running sessions, and supporting hands-on adoption of AI tools
• Evaluate emerging tools and technologies, balancing experimentation with practical implementation
• Contribute to improving team efficiency through the use of AI-assisted development tools and workflows
• Monitor and assess the effectiveness of AI implementations, iterating based on feedback and outcomes
• Where appropriate, support the safe and responsible use of AI, including data handling, prompt safety, and output validation

Person Specification & Skills

• Experience working with AI/ML technologies, particularly LLMs and modern AI tooling
• Practical experience building or integrating AI-enabled applications (e.g. RAG, chat interfaces, AI-assisted workflows)
• Strong understanding of prompt design, evaluation, and techniques to improve output quality and consistency
• Experience working with APIs and integrating external services into applications
• Familiarity with concepts such as vector databases, embeddings, and information retrieval
• Understanding of software development practices and how AI fits into the development lifecycle
• Ability to collaborate effectively with engineering, product, and design teams
• Strong problem-solving skills and a practical approach to experimentation and delivery
• Comfortable working in a fast-evolving space with changing tools and approaches
• Strong communication skills, with the ability to explain AI concepts and approaches clearly
• Experience using AI-assisted development tools (e.g. Copilot, Claude Code or similar), or supporting others in their adoption
• Hands-on software development experience (e.g. TypeScript, Python, or similar) is beneficial but not essential