Tech stack:

• Microsoft Azure AI Services (e.g. Azure OpenAI, Cognitive Services)

• Machine Learning frameworks (conceptual understanding or hands-on exposure)

• Data platforms (e.g. Azure Data Lake, Databricks, Synapse – nice to have)

• Search & retrieval technologies (e.g. vector search, RAG architectures)

• Azure DevOps / Jira (Agile delivery and backlog management)

• Power BI / Excel (data analysis and reporting)

• M365 Suite (Teams, SharePoint, PowerPoint)

• Optional: Python / SQL (for data analysis or prototyping)

Requirements:

• Minimum 4 years of experience in:

  • AI-enabled transformation programmes (including GenAI, Machine Learning, or Decision Intelligence)

  • Redesigning end-to-end business processes leveraging AI

  • Eliciting and documenting AI-related requirements and use cases

  • Delivering AI solutions into production environments

  • Integrating AI services within enterprise ecosystems (e.g. Azure AI, data platforms)

  • Performing data analysis with strong focus on data quality and governance

  • Designing complex decision processes combining human and AI inputs

• Strong understanding of AI/ML concepts and enterprise AI architectures

• Expertise in decision intelligence and process optimisation

• Ability to translate business problems into AI-driven solutions

• Strong analytical and data-driven mindset

• Excellent stakeholder management and communication skills

• Experience working in complex, regulated, or multi-stakeholder environments

Nice to have:

• Experienced in using AI tools in day-to-day workflow

Project description:

• Support of complex data, process, and AI transformation programmes (e.g. EFSA context)

• Focus on leveraging AI (including GenAI and Machine Learning) to redesign business processes, enable intelligent decision-making, and deliver scalable AI solutions

• Work within enterprise environments with strong alignment to organisational goals

• Act as a bridge between business stakeholders, data teams, and technical teams

• Ensure successful deployment of AI solutions into production environments

Main responsibilities:

• Drive AI-enabled transformation initiatives across complex business domains

• Elicit, analyse, and document AI use cases, requirements, and business needs

• Lead end-to-end process redesign, integrating AI capabilities to enhance efficiency and decision-making

• Design and support implementation of AI-driven decision models combining human and machine inputs

• Contribute to delivery and deployment of AI components into production environments

• Support integration of AI services within enterprise architectures, including cloud-based solutions (e.g. Azure)

• Perform data-driven analysis with strong focus on data quality, integrity, and governance

• Collaborate with multi-disciplinary stakeholders (business, IT, data teams, external providers)

• Ensure alignment with enterprise standards, governance, and security frameworks

• Provide structured business analysis support across data, process, and AI transformation initiatives