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)

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

About Spyrosoft

Spyrosoft is an authentic, cutting-edge software engineering company, established in 2016. In 2021 and 2022, we were among the fastest growing technology companies in Europe, according to the Financial Times. We were founded by a group of tech experts with established backgrounds in software engineering, who created an ‘engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships. Having a unique offering, which bridge the gap between technology and business, we specialise in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education and financial services industries.

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

0 openings across locations