AI Engineer (Graduate)

Role Summary

As a Graduate AI Engineer at Avanade, you will help design, build, and deploy AI-powered solutions that transform how organizations work. Working alongside experienced consultants and engineers, you will develop applications using Generative AI, AI Agents, Azure AI technologies, and modern data platforms to solve real business problems.

Key Responsibilities

• Develop AI-powered applications using Azure AI Foundry, Azure OpenAI, and modern cloud technologies.

• Build and test AI Agents, copilots, and agentic workflows that automate tasks and enhance decision-making.

• Support the implementation of Generative AI, Retrieval-Augmented Generation (RAG), and machine learning solutions.

• Collaborate with business and technical teams to translate requirements into innovative AI solutions.

• Apply Responsible AI, security, and governance practices throughout the solution lifecycle.

• Continuously learn and contribute to Avanade's AI innovation community.

Why Avanade? Because there’s literally no place like this

We have two parent companies that give us a strong Microsoft ecosystem with space to be ourselves.  People who thrive here are motivated, interested in learning and genuinely have a desire to be the best at what they do. If that sounds like you, then we’re the perfect match. You will have the opportunity to utilize the most advanced technology within the Microsoft ecosystem, collaborating with some of the world's largest and most renowned companies, as well as working alongside highly intelligent individuals. This environment allows you to make a significant impact on your career trajectory. If you are looking to enhance your skills and drive transformation within businesses, there is no better place to be.

The EME AI Delivery Hub

AI—and particularly Generative AI—is expected to profoundly impact every company over the coming years. Thanks to Microsoft and Avanade’s strategic investments in AI and OpenAI, we are uniquely positioned to help our clients become AI-first organizations.

The EME AI Delivery Hub is an Iberia-based nearshore delivery center serving European and Middle Eastern clients, specialized in end-to-end AI and Advanced Analytics solutions. By joining the Hub, you will be part of a delivery pod working in an agile setup, owning AI initiatives from problem framing and data exploration to model development, deployment, and adoption. You will work closely with clients, guiding them throughout their AI and GenAI transformation journey.

Job Overview

As a Senior Analyst – AI & Data Science, you will design, develop, and deliver AI- and data-driven solutions that help our clients achieve measurable business outcomes. This role combines strong Data Science foundations with hands-on AI engineering, including recent GenAI use cases.

You will work across the full data science lifecycle: data exploration, feature engineering, model development, evaluation, and deployment, while also contributing to modern AI solutions such as LLM-based applications, NLP, computer vision, and predictive analytics, primarily on Microsoft Azure.

Key Role Responsibilities

Day-to-day you will:

• Design and deliver end-to-end Data Science and AI solutions, from business understanding and data exploration to model deployment and monitoring.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing on structured and unstructured datasets.
• Develop, train, evaluate, and optimize machine learning and deep learning models, selecting appropriate algorithms and validation strategies.
• Contribute to Generative AI solutions, including LLM-based applications, prompt engineering, RAG architectures, and applied NLP use cases.
• Translate business problems into analytical and ML formulations, clearly explaining trade-offs and results to both technical and non-technical stakeholders.
• Support the preparation of client presentations, demos, and proposals, articulating analytical insights and AI-driven value.
• Stay up to date with the latest advancements in Data Science, ML, DL, and GenAI, and actively share knowledge within the team.
• Contribute to reusable assets such as code templates, analytical frameworks, and internal training materials.
• Collaborate with senior team members and architects to identify opportunities where advanced analytics and AI can transform client operations.