Senior AI Agent & LLM Architect

Genixbit; San Francisco, Northern (CA, KY); Hybrid; USD 185,000 - 245,000; Full time

Job summary

Genixbit is seeking a Senior AI Agent & LLM Architect to design production-grade multi-agent cognitive networks and autonomous reasoning loops for enterprise automation.

You will deploy open-source LLMs, optimize vector pipelines, and lead latency and safety evaluations across AWS GPU clusters, shaping scalable AI infrastructures.

Qualifications

• 5+ years in AI engineering, NLP, or distributed systems development
• Hands-on mastery of Python, PyTorch, LangChain/LangGraph, and Pinecone/Qdrant
• Proven track record of shipping autonomous multi-agent networks in production
• Strong expertise in vector embeddings and enterprise API integration

Responsibilities

• Architect resilient multi-agent orchestration frameworks using LangGraph, CrewAI, and AutoGen
• Optimize vector indexing, context-window retrieval, and prompt guardrails
• Deploy open-source LLMs (Llama 3, Mistral, Qwen) with vLLM on AWS GPU clusters
• Conduct system evaluations for latency, safety guardrails, and accuracy

Skills

Python

PyTorch

LangChain

LangGraph

Vector embeddings

API integration

Open-source LLMs

Tools

CrewAI

AutoGen

vLLM

Pinecone

Qdrant

Job description

Senior AI Agent & LLM Architect

Full-time San Francisco USA Hybrid Senior $185,000 - $245,000 / year Posted: Sep 12, 2026 · Closes: Oct 2, 2026

About the Role

Design and deploy production-grade multi-agent cognitive networks, RAG memory pipelines, and autonomous reasoning loops for enterprise automation.

Key Responsibilities

• Architect resilient multi-agent orchestration frameworks using LangGraph, CrewAI, and AutoGen
• Optimize vector indexing, context-window retrieval, and prompt guardrails
• Deploy open-source LLMs (Llama 3, Mistral, Qwen) with vLLM on AWS GPU clusters
• Conduct system evaluations for latency, safety guardrails, and accuracy

Requirements

• 5+ years in AI engineering, NLP, or distributed systems development
• Hands-on mastery of Python, PyTorch, LangChain/LangGraph, and Pinecone/Qdrant
• Proven track record of shipping autonomous multi-agent networks in production
• Strong expertise in vector embeddings and enterprise API integration