- 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 and keyword search
- Process, clean, and structure source information to improve the accuracy and relevance of AI-generated 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
- Own changes end-to-end, including design, implementation, testing, and deployment
- Work independently while proactively communicating blockers, scope questions, and technical trade-offs
- 3+ years of commercial software development experience
- 2+ years of experience working on AI/ML projects
- Good Python skills with hands-on implementation experience
- Practical experience with LLMs and modern AI technologies
- Practical experience with RAG architecture, vector embeddings, and hybrid search
- Experience with information processing aimed at improving AI quality, including data preparation, chunking, metadata enrichment, and relevance tuning
- Ability to work independently and take ownership of tasks from design through deployment
- Upper-Intermediate English
WILL BE A PLUS
- Experience with knowledge graphs or graph databases
- Background in the telecommunications domain