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Enterprise Knowledge Base with Conversational AI Search

AI / Cloud EngineerDmytro B.
Dmytro B.
Dmytro B.

AI / Cloud Engineer

LLM & AI Agents

Key Expertise

Vector Similarity SearchGenerative AI SolutionsMulti-tenant RAG SystemsEnterprise Data Sync

Experience

6+ years

Timezone

CET (UTC +1)

Skills

AI / ML

Vertex AI SearchMatching EngineSpeech-to-TextGeminitext-embeddingGoogle Vertex AIDiscovery Engine

Languages

Python

Databases

RedisPostgreSQL

Infrastructure

NginxCloud Storage (GCP)Docker Composeoauth2-proxyDocker

Frameworks

FastAPIaiogramCelery

Integrations & Protocols

LibreOfficeGoogle Workspace OAuth
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Overview

Built an AI-powered knowledge base for a large logistics company group (5 subsidiaries). The system syncs thousands of PDFs from Google Drive, indexes them in Vertex AI Search, and provides employees with conversational AI search - delivering answers with citations from corporate documentation.

Achievements

Manages 6 isolated datastores across 5 companies with 10 Drive source folders. Multi-turn conversations with context retention. Parallel async API calls reduce first-query latency significantly.

Responsibilities

  • Architected multi-tenant RAG system with per-company datastores, buckets, and Drive folder mappings
  • Implemented full document lifecycle: Drive → GCS → Discovery Engine with incremental sync and deletion cleanup
  • Built Celery Beat periodic sync with retry logic and repository pattern
  • Developed conversational search with persistent sessions and structured citation extraction
  • Implemented multi-language detection (9 languages) to override Discovery Engine's auto-detection

Technologies Used

PythonFastAPICeleryRedisPostgreSQLDiscovery EngineCloud Storage (GCP)Google Workspace OAuthDockerNginxVertex AI Search
Dmytro B.

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Dmytro B.

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