Custom Field 3: 17308

AI Engineer (Group IT)

The Group IT Data Team's vision is to establish scalable, enterprise-grade AI solutions that enhance operational efficiency, unlock new business value, and accelerate digital transformation across business units. The team consists of forward-thinking engineers, data specialists, and technologists, working closely with business stakeholders to deliver impactful AI-driven solutions.

The AI Engineer is responsible for designing, developing, and deploying AI-driven applications, with a primary focus on Generative AI (GenAI) and Large Language Models (LLMs).

The role will collaborate with business and technology teams to identify use cases, translate requirements into AI solutions, and deliver scalable, secure, and production-ready applications. Over time, the role will also expand into broader machine learning and advanced analytics initiatives.

Responsibilities

Design, develop, and deploy GenAI/LLM-based applications such as copilots, chatbots, search, and knowledge assistants.
Work with enterprise platforms (e.g., Azure OpenAI, Azure AI Services, SAP AI capabilities) to build and integrate AI solutions.
Translate business use cases into AI solution architectures, including prompt design, orchestration, and API integration.
Able to conduct data analysis and data engineering/modelling to prepare data for model training.
Develop and manage end-to-end AI pipelines, including data ingestion, preprocessing, embedding, model interaction, and output validation.
Collaborate with cross-functional teams (business users, IT, vendors) to ensure AI solutions align with operational needs and enterprise architecture.
Ensure responsible AI practices, including governance, security, data privacy, and model evaluation.
Improve and maintain AI systems for performance, scalability, and cost efficiency.
Stay updated with emerging AI technologies and continuously enhance the organization's AI capabilities.
Gradually expand into machine learning model development, predictive analytics, and advanced data science use cases.

Requirements

Degree in Computer Science, Information Technology, Engineering, or equivalent, with at least 2–5 years of experience in software engineering, data engineering, or AI/ML-related roles.
Hands-on experience or strong exposure to GenAI/LLM technologies (e.g., Azure OpenAI, LangChain, prompt engineering).
Familiarity with cloud platforms (preferably Azure) and API-based system integration.
Experience in programming languages such as Python, JavaScript, or similar.
Understanding of data concepts including data pipelines, embeddings, vector databases, and APIs.
Proficiency in advance SQL and major data platforms (relational, cloud data warehouse and big data tools)
Strong problem-solving skills with the ability to translate business needs into technical solutions.
Exposure to SAP ecosystem or enterprise systems integration is an advantage.
Understanding of machine learning concepts and willingness to grow into ML model development.
Strong communication skills and ability to work effectively in cross-functional teams.
Self-driven, adaptable, and keen to learn emerging AI technologies.