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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10 applications
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