What You'll Do
Design and implement generative AI solutions on modern cloud environments, including platforms such as Microsoft Azure AI Foundry. Translate client needs into functional AI applications by working across the full project lifecycle—from concept to deployment.
Focus on advanced techniques like Retrieval Augmented Generation (RAG) and the development of domain-specific AI agents. Contribute to automating complex business processes using agentic architectures, ensuring solutions are both scalable and effective.
Engage directly with client stakeholders to understand operational challenges and align technical development with business outcomes. Your work will bridge technical innovation and practical application, delivering measurable impact.
Requirements
- Minimum of one year’s experience building and deploying AI solutions, particularly involving large language models (LLMs) and RAG, on cloud AI platforms such as Microsoft Azure AI Foundry or equivalent
- At least two years of hands-on programming experience with Python or other relevant languages
- Strong interest in software development and a collaborative mindset for working closely with business teams
- Fluent written and spoken proficiency in both Swedish and English
Preferred Qualifications
- Background in advanced analytics or data science, including statistical modeling and machine learning applications
- Experience with traditional business intelligence tools and methods, including data warehousing, relational databases, data modeling, and visualization platforms such as Power BI
Technical Environment
You'll work with a modern stack centered on generative AI technologies, including Microsoft Azure AI Foundry, RAG frameworks, AI agent development, and agentic automation. Supporting tools include Python for development, relational data systems, and Power BI for insights delivery.
Benefits
- Opportunity to shape cutting-edge AI projects from initial idea through to delivery
- Supportive environment that encourages both personal and professional growth, backed by experienced colleagues
- Hybrid work model allowing flexibility between on-site and remote work based on project needs
- Active role in influencing client outcomes and advancing organizational capabilities in generative AI
