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About the role
Key responsibilities & impact- Lead the technical development of LLM-based solutions.
- Design end-to-end architectures for processing and understanding unstructured data: data ingestion; parsing and transformation; retrieval and RAG; reasoning and extraction.
- Decide when to use agents versus deterministic pipelines.
- Ensure quality, scalability, and observability of solutions in production.
- Evolve technical standards, architecture, and best practices for the AI stack.
- Mentor other engineers and raise the team's technical level.
- Work closely with product to turn complex problems into incremental solutions.
Requirements
What you’ll need- Strong software engineering (backend) experience — 5+ years.
- Hands-on experience with AI systems in production (especially LLMs).
- Experience building applications with RAG, agents, or information extraction.
- Familiarity with frameworks such as Agno, LangChain, LlamaIndex, or similar.
- Experience designing distributed, scalable system architectures.
- Experience processing unstructured data.
- Knowledge of embeddings, semantic search, and response quality evaluation.
- Experience with observability and debugging of AI systems.
- Proficiency with Git.
Benefits
Comp & perks- Meal allowance / food voucher
- Childcare assistance
- Remote work
- Health insurance
- Education and cultural benefits
- Gympass membership
- Birthday day off
- Discounts on therapy
- English courses
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
software engineeringAI systemsLLMsRAGinformation extractiondistributed system architecturesunstructured data processingembeddingssemantic searchresponse quality evaluation
Soft Skills
mentoringproblem-solvingteam collaboration
