Applied AI / LLM Engineer (Python)

Role overview

Responsibilities

• check_circle Design and build LLM pipelines, AI agents, and RAG-based systems: function/tool calling, structured output (JSON schema)
• check_circle Develop production-grade Python services (Django, Celery, Redis)
• check_circle Validate product hypotheses using real-world data and analytics
• check_circle Measure and optimize LLM quality, performance, and cost
• check_circle Collaborate closely with product managers and engineers to turn ideas into scalable solutions

Basic qualifications

• Strong experience building production LLM applications
• Hands-on expertise with RAG, embeddings, vector search, prompt engineering, and LLM evaluation
• Experience with LangGraph, LangChain, or similar frameworks
• Solid Python backend background (Django, PostgreSQL, async programming)
• Strong SQL/Pandas skills and a data-driven mindset
• Language Proficiency: English at B2-C1 level, Russian at C1 level
• Location*<em>:</em>* any, except Russia and Belarus

Preferred qualifications

• Experience with vector databases (Qdrant, pgvector, etc.)
• Fine-tuning, text classification, or embedding models
• Kubernetes, gRPC, or Go experience

Benefits

• check_circle Flexible working hours
• check_circle Remote-first culture
• check_circle Long-term projects
• check_circle Salary in dollars
• check_circle Professional communities
• check_circle Onsite business trips
• check_circle Training budget
• check_circle Paid conferences

About the company