Senior LLM Systems / Agent Infrastructure Engineer

Job Description

We are hiring a Senior LLM Systems / Agent Infrastructure Engineer to optimize and scale a production multi-agent LLM system that translates natural language into Cypher / SQL queries, executes guarded graph retrieval, and synthesizes structured RAG responses. You will engineer a faster, cheaper, and more reliable LLM system in production.

 

What We’re Building

A production multi-agent LLM system that:

  • Converts Natural Language (NL) → Cypher (Neo4j) / SQL (PostgreSQL)
  • Executes guarded graph queries
  • Runs structured Retrieval-Augmented Generation (RAG)
  • Orchestrates used tools

 

What You’ll Own

  • Cut NL → Cypher / SQL latency
  • Optimize model routing & tool orchestration
  • Replace unnecessary LLM calls with deterministic logic
  • Redesign context strategy
  • Evaluate / replace current LLM stack (Google ADK)

Outcome: A faster, cheaper, and more stable pipeline.

 

Required

  • 5+ years backend / ML systems experience
  • 2+ years production LLM pipelines experience
  • Strong Python (async, FastAPI)
  • Experience with agent frameworks (LangGraph, DSPy, Semantic Kernel, etc.)
  • Structured outputs / function calling
  • RAG over structured data
  • LLM + SQL or graph DB integration
  • Strong grasp of token economics & latency optimization
  • Inference optimization (vLLM, batching, streaming)

Required skills experience

AI/ML API 5 years
LLM 5 years
Big Data 5 years

Required domain experience

Machine Learning / Big Data 5 years

Required languages

English C1 - Advanced
Python, Machine Learning, LLM, LLM/Llama/Mistral/GPT/RAG/FAISS, Multi-agent LLMs, LLM & AI Agents:, LLM Integration, LLM tuning, LLM-tools, OpenAI/LlamaIndex/LLaMa/Moralis/LangChain/LLM/LLMOps
Published 10 February
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