AI Developer

Ework Group, founded in 2000 and listed on Nasdaq Stockholm, has around 13,000 independent specialists delivering projects. It is a comprehensive talent management solutions provider working with private and public sector clients, focusing on IT/OT, R&D, engineering, and business development. The company builds sustainable talent supply chains and delivers lasting value through a holistic and independent approach to talent management.

• Experience working with Azure AI/ML services including Azure AI Foundry/Studio, Azure OpenAI, Azure AI Search, Azure Machine Learning, model registries, monitoring, and evaluation.
• Strong programming skills in Python (preferred) or .NET (C#) for creating services, SDK/REST, and automated tests.
• Experience with RAG (vectors, indexes, document normalization) and prompt engineering practices.
• MLOps/DevOps experience for AI: repositories (Git), pipelines (Azure DevOps/GitHub Actions), Infrastructure as Code (Bicep/Terraform), reusable artifacts.
• Experience with advanced document splitting and preprocessing techniques (recursive/semantic/layout-aware chunking).
• Experience with advanced document retrieval methods (multi-step retrieval).
• Experience with re-ranking and improving quality of agent-based solution responses.
• Experience in cost optimization of RAG solutions.
• Experience deploying RAG solutions at large scale.
• Knowledge transfer and AI competency development within teams, including preparing technical documentation, solution patterns, and best practices.

Nice to have:

• Experience with AI agents (e.g., orchestration/agent frameworks, agent evaluation).
• Integration with APIM, Functions, AKS/ACI, reliability patterns (retry, circuit breaker).
• Experience in data security (PII, GDPR, red teaming for LLM, content filtering).

• Design, implement, and maintain AI/LLM services on Azure (inference, flow orchestration, RAG, agents).
• Create and optimize prompts, manage versioning, evaluate and monitor model response quality.
• Integrate with domain systems (APIs), build MLOps and CI/CD pipelines for AI/ML components.
• Ensure compliance with Data & AI Governance frameworks including AI Act requirements for high and limited risk solutions through documentation, human oversight, testing, and transparency.
• Optimize costs and reliability (observability, alerting, SLO/SLA), support production incidents.
• Collaborate with product owners, architects, legal, and security teams from concept to rollout.
• Build and develop knowledge bases used by AI solutions, including structuring, versioning, updating, and integration with language models.
• Design and implement AI solutions at the intersection of Azure AI Foundry, Power Platform (Power Apps, Power Automate, Copilot Studio), and RPA (UiPath).
• Transfer knowledge and develop AI competencies within the team, prepare technical documentation, solution patterns, best practices, and support team members in building and maintaining AI-based solutions.