AI SummaryVerified by Aipplify AI
The vacancy is clear in tasks and requirements but lacks company information and detailed compensation structure.
AI quality score6.7 / 10
Check Match — Just drop your CV
See your fit for LLM Engineer in seconds.
Overview
We are looking for an LLM Engineer to manage knowledge bases and optimize LLM pipelines. Responsibilities include API debugging, token economy management, and ensuring integration stability.
Responsibilities
- •Gather and maintain knowledge bases/data for LLM pipelines (structure, quality, updates)
- •Debug LLM API and internal services: errors, retries, limits, stability
- •Optimize token usage: prompts, context, cache/checkpoints, model selection, cost control
- •Bring integrations to a working state in production (logs, metrics, reproducible runs)
Conditions
- •Payment 4 times a month
- •Salary negotiable, starting from 80,000 ₽
- •Specific tasks: databases → API → token economy, with measurable results
Requirements
- •Python (scripting, services, debugging)
- •Experience with LLM API (OpenAI-compatible or equivalents)
- •Databases/storage of artifacts (SQLite/Postgres or file indexes)
- •Understanding of token economics: excess tokens, context duplication, repeated calls
- •Attention to detail: do not break the pipeline, document changes, verify results
Loading similar jobs...