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AI Engineer - Agentic AI Platform

CÔNG TY CỔ PHẦN UDATA · Hà Nội
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Type
Full-time
Work mode
On-site
Level
Staff
Industry
Engineering / Mechanical
Salary
Thương lượng
Location
Thành phố Hà Nội, Hà Nội

Overview

  • Build and maintain LangGraph agents (ReAct pattern) that orchestrate multi-step reasoning across ERP, WMS, and accounting data.
  • Develop MCP connectors (FastMCP 2.x) to integrate external business APIs — NetSuite SuiteQL, Base.vn, MS365, Google Workspace.
  • Design agent skills (prompt engineering + output schemas) for inventory analysis, cash flow forecasting, dead stock detection, and supplier signal extraction.
  • Build document ingestion pipelines: PDF, Word, Excel → structured data — layout parsing, table extraction, OCR for scanned documents.
  • Build RAG pipelines to let agents retrieve from internal docs (SOPs, product catalog, historical alerts) to explain decisions and suggest next steps.
  • Work with the LLM gateway (LiteLLM) to manage model routing, cost guardrails, and observability (Langfuse tracing).
  • Build async Python services (FastAPI) and wire agent-to-agent communication via Redis Streams.
  • Write unit tests for engine logic and integration tests with real Postgres + Redis (testcontainers).
  • 1–3 years Python experience, comfortable with async (async/await, httpx, FastAPI).
  • Hands-on with LangGraph or LangChain agents — tool calling, state machines, multi-step reasoning.
  • Understands LLM patterns: prompt engineering, tool use, structured output (Pydantic), context window management.
  • Familiar with RAG: embeddings, vector search (pgvector / Qdrant), chunking strategies, retrieval quality evaluation.
  • Experience with document processing: PDF/Word/Excel parsing, OCR (PaddleOCR / Surya), layout analysis (Docling, PyMuPDF), table extraction.
  • Can read and integrate REST APIs with auth (OAuth1/2, API keys).
  • Writes production-ready code: type hints, tests, clear error handling.
  • Experience with FastMCP / MCP protocol.
  • Familiarity with Redis Streams or other event buses.
  • Exposure to multi-agent orchestration (supervisor pattern, A2A communication).
  • Agent evaluation: LLM-as-judge, tool call precision, trajectory eval.
  • Tool design patterns: idempotency, retry strategies, error recovery.
  • Domain knowledge in ERP, inventory, or cash flow management.

Benefits

Stock options / ESOP

Summary of facts from the official posting. View original ↗

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