ppThe AI Engineer is a hands-on, early-career role responsible for designing, developing, and deploying AI solutions, including Machine Learning, Deep Learning, and Generative AI applications, that address real business challenges and deliver measurable value. Working within the Data Digital Innovation team, the AI Engineer builds and optimizes AI applications using LLMs, RAG architectures, agents, and predictive models, and engineers the surrounding software (micro-services, APIs, and data integrations) required to bring them into production. The role combines solid software engineering fundamentals with applied AI expertise, collaborating closely with senior engineers, architects, and business stakeholders to turn prototypes into robust, scalable, enterprise-grade solutions, while continuously evaluating and adopting emerging AI technologies and best practices. /p h3Key Accountabilities /h3 ul liDesign, develop, and deploy AI solutions, including Machine Learning, Deep Learning, and Generative AI applications. /li liBuild and optimize AI applications using LLMs, RAG architectures, agents, and predictive models. /li liDesign and deploy applications with a micro-services architecture that integrate with enterprise systems, APIs, and databases. /li liWrite high-quality, scalable, and maintainable code, contributing across all phases of the software development lifecycle. /li liTransition proofs of concept and prototypes into production-ready solutions, with a focus on performance, reliability, and security. /li liEvaluate and adopt new AI technologies, frameworks, and best practices, incorporating them into solution design where appropriate.



/li liApply modern engineering and DevOps practices (version control, CI/CD, and containerization) to ensure robust, repeatable deployments. /li liCollaborate with senior engineers, architects, and business stakeholders to align solutions with requirements and enterprise architecture standards. /li /ul h3Networking/Key relationships /h3 ul liWorks closely with AI/ML leads and senior engineers within the Data Digital Innovation team for technical guidance, code reviews, and mentoring. /li liCollaborates with data scientists and data analysts to operationalize models and deliver data-driven products. /li liEngages with enterprise and solution architects to ensure solutions align with enterprise architecture standards. /li liPartners with IT, SAP, and platform teams to integrate AI applications with enterprise systems, APIs, and databases. /li liCoordinates with cybersecurity architects to ensure solutions meet security and compliance requirements. /li liInteracts with business stakeholders to gather requirements, validate outcomes, and demonstrate business value. /li /ul h3Minimum Knowledge Experience required for the position: /h3 ul liBachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, or a related technical field. /li li2–3 years of experience designing, building,



and deploying AI/ML or software solutions in a professional environment. /li liSolid proficiency in Python and AI frameworks such as TensorFlow, PyTorch, and scikit-learn. /li liWorking knowledge of AI, Generative AI, and prompt engineering fundamentals, including LLMs, RAG architectures, agents, and predictive models. /li liHands-on experience with AWS cloud services such as S3, Lambda, EC2, Bedrock, and SageMaker. /li liExperience with core software engineering tools and practices, including Git and GitHub Actions, Docker, Kubernetes, and REST APIs. /li liManagement has the discretion of substituting relevant work experience for a degree and/or making exceptions to the years of experience requirement. /li /ul h3Skills Capabilities: /h3 ul liStrong programming foundations and clean-code discipline, particularly in Python. /li liApplied understanding of machine learning, deep learning, and generative AI techniques. /li liAbility to design micro-services and integrate solutions with enterprise systems, APIs, and databases. /li liCuriosity and a research mindset, with eagerness to experiment with and learn emerging methods. /li liSolid problem-solving, analytical, and debugging skills. /li liEffective collaboration and communication across technical and non-technical audiences. /li liAbility to prioritize and execute in fast-moving, ambiguous contexts. /li liStrong commitment to quality, reliability, and security in delivered solutions. /li /ul pTravel is expected up to 10% of the time to support collaboration, team engagement, and stakeholder meetings. /p /p #J-18808-Ljbffr

📌 AI Engineer (Barcelona)
🏢 Werfen
📍 Barcelona