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Company Description
Our customer is a leading Swedish telecommunications company, recognized for delivering innovative large-scale technology solutions across complex infrastructure environments. Sweden's telecom sector is known for its advanced networks, high-speed connectivity, and pioneering role in 5G development. The company operates internationally, serving millions of users and partnering with global technology leaders to drive digital transformation.

Job Description
You will join one of two AI initiatives: ChatCPI, an LLM-powered assistant for intelligent search and question answering over large technical documentation, or a Knowledge Graph Platform focused on structuring and connecting enterprise information for AI-driven use cases.

What you will do
Design and implement LLM-based features and RAG pipelines, from data ingestion to answer generation
Build and optimize retrieval using vector embeddings and hybrid (semantic + keyword) search
Process, clean and structure source information to improve the accuracy and relevance of AI output
Evaluate model quality, experiment with new approaches and bring proven solutions into production
Work closely with the team to integrate AI components into the wider platform

What we expect
3+ years of experience on AI/ML projects
Strong Python skills and hands-on implementation experience
Solid understanding of the modern AI stack, LLMs and current industry developments
Practical experience with RAG architecture, vector embeddings and hybrid search
Experience with information processing aimed at improving AI quality (data preparation, chunking, metadata enrichment, relevance tuning)

Ways of working
Comfortable owning a change end-to-end: design, implement, test, and deploy.
Can work independently but communicates proactively when blocked or when scope/tradeoffs need a decision
Experience working in an Agile team will be considered a plus
Soft skills: since this is a fully remote position, we expect a highly proactive attitude – showing results, actively participating in all initiatives, etc

Nice to have
Experience with knowledge graphs or graph databases
Background in the telecom domain

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