
51 - 200 employees
We deliver 100% data quality with zero manual maintenance for data-driven organizations. 🍒 𝗛𝗼𝘄?➡️ Powered by sharing➡️ Enabled by software solutions ➡️ Supported by research We emerged from the University of St. Gallen in Switzerland and are a proud global pioneer in data sharing with more than 18 years of data management expertise. By automating business partner data management processes, you can avoid the error-prone manual work of creating and maintaining data. We support your business partner master data activities from data assessment, normalization, merging, and quality assurance to fraud prevention, bank account trust scoring, and sanctions checks. 🍒 𝗪𝗵𝘆 𝗰𝗵𝗼𝗼𝘀𝗲 𝗖𝗗𝗤?Leading global enterprises, such as Bayer, Tetra Pak, Nestle, and many more Global Fortune 2000 companies rely on CDQ software solutions to better solve data challenges and benefit from exchange of best practices within the CDQ Data Sharing Community. With CDQ, you access the world of external business partner data (+70 external registers and premium data sources available on our CDQ Cloud Platform) and a gateway to connect to any business application (e.g. SAP MDG) with a set of more than 2500 ready-to-use data quality rules. In partnership with market leaders, we deliver master data automation for intelligent enterprises, offering a seamless integration for accessing accurate business partner information. ➡️ Our solution CDQ First Time Right has been officially endorsed by SAP. ➡️ Gartner’s Magic Quadrant recognized CDQ approach in the Interenterprise MDM category. ➡️ CDQ solutions offer a high level of customization, featuring a rule-based engine and adaptable APIs that you can effortlessly integrate directly into your existing ERP, CRM, and SRP systems. Experience the difference with CDQ and unlock the full potential of your master data management!
🔥 0 minutes ago
🗣️🇵🇱 Polish Required
Improve your chances of getting an interview by checking your resume score before you apply.

51 - 200 employees
We deliver 100% data quality with zero manual maintenance for data-driven organizations. 🍒 𝗛𝗼𝘄?➡️ Powered by sharing➡️ Enabled by software solutions ➡️ Supported by research We emerged from the University of St. Gallen in Switzerland and are a proud global pioneer in data sharing with more than 18 years of data management expertise. By automating business partner data management processes, you can avoid the error-prone manual work of creating and maintaining data. We support your business partner master data activities from data assessment, normalization, merging, and quality assurance to fraud prevention, bank account trust scoring, and sanctions checks. 🍒 𝗪𝗵𝘆 𝗰𝗵𝗼𝗼𝘀𝗲 𝗖𝗗𝗤?Leading global enterprises, such as Bayer, Tetra Pak, Nestle, and many more Global Fortune 2000 companies rely on CDQ software solutions to better solve data challenges and benefit from exchange of best practices within the CDQ Data Sharing Community. With CDQ, you access the world of external business partner data (+70 external registers and premium data sources available on our CDQ Cloud Platform) and a gateway to connect to any business application (e.g. SAP MDG) with a set of more than 2500 ready-to-use data quality rules. In partnership with market leaders, we deliver master data automation for intelligent enterprises, offering a seamless integration for accessing accurate business partner information. ➡️ Our solution CDQ First Time Right has been officially endorsed by SAP. ➡️ Gartner’s Magic Quadrant recognized CDQ approach in the Interenterprise MDM category. ➡️ CDQ solutions offer a high level of customization, featuring a rule-based engine and adaptable APIs that you can effortlessly integrate directly into your existing ERP, CRM, and SRP systems. Experience the difference with CDQ and unlock the full potential of your master data management!
• Designing and implementing AI agents with reasoning pipelines (e.g., multi-step workflows, RAG-based decision making) • Integrating AI capabilities such as LLM-powered services, semantic search, and intelligent automation • Contributing to scalable architectures for data- and event-driven systems • Improving, refactoring, and maintaining existing code bases • Designing tasks in collaboration with the Team Lead and Product Owner • Participating in code reviews, architecture discussions, and knowledge sharing
• 5+ years of professional experience • Java • Spring Boot • Docker • AI-related: Spring AI • Experience integrating LLMs into applications (OpenAI API, Anthropic, local inference, etc.) • Understanding of vector databases (Milvus, Pinecone, Qdrant, Elasticsearch) • AWS Bedrock • LangChain4j • Knowledge of embeddings, prompt engineering basics, and retrieval-augmented generation (RAG) • Understanding Model Context Protocol • Polish – C1 (required) • English – C1/B2+ (required)
• Professional development • Collaboration with the Team Lead and Product Owner
Apply Now🔥 7 hours ago
Senior Engineer developing and deploying GenAI applications for a leading global consulting firm. Collaborating across AI applications and scaling solutions for enterprise systems.
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Microservices
Python
🕒 3 days ago
Senior AI Engineer at Sigma Software developing scalable AI-driven systems for EdTech solutions. Working with advanced technologies like AI and semantic graphs in a remote, flexible environment.
Apache
AWS
Azure
Cloud
ETL
Google Cloud Platform
Kubernetes
Spark
Go
🕒 3 days ago
AI Inference Engineer developing efficient on-device AI systems for edge devices. Collaborating with researchers and integrating AI features into existing products at ITRex.
C++
JavaScript
🕒 June 20
1001 - 5000
Lead AI Engineer at Kainos bridging data science and software engineering. Collaborate with teams to deliver AI solutions for Workday products.
AWS
Azure
Cloud
Docker
Google Cloud Platform
Java
Python
🕒 June 10
AI Engineer at InPost driving innovative solutions with Generative AI models for web applications. Collaborating in an international environment focusing on sustainable delivery solutions.
🗣️🇵🇱 Polish Required
AWS
Azure
Cloud
Docker
Google Cloud Platform
Kubernetes
Microservices
NoSQL
Python
Redis
SQL