Staff AI-Native Systems Engineer (LLM Agents)

chamberlain; Oak Brook (IL); On-site; USD 180,000 - 300,000; Full time

Job summary

Chamberlain Group is seeking an experienced AI software engineer to architect and build LLM-based agents that integrate with real-world tools and APIs. You will design systems that orchestrate tasks across roles and scale in production environments.

You will lead cross‑functional teams, drive tooling decisions, and mentor engineers in AI-native patterns, with a focus on reliability, observability, and fast-paced delivery within a large, established company.

Qualifications

• 10+ years of software engineering experience, with at least 2+ years in LLMs or agentic AI systems.
• Proven experience building LLM-powered agents that interact with external tools and APIs.
• Experience with agent orchestration frameworks (LangGraph, CAMEL, AutoGen).
• Experience leading AI productization, intelligent automation, or AI-native UIs.
• Experience with AI infrastructure, prompt engineering, or fine-tuning LLMs is a strong plus.

Responsibilities

• Oversee AI feature development in Chamberlain products such as video-based search and chat interfaces.
• Architect and build agentic AI systems with LLMs, RAG, tool integration, and orchestration.
• Design layouts where agents collaborate via coordination protocols and memory management.
• Develop pipelines using LangChain, LangGraph, CAMEL, and related tools.
• Ensure scalable, reliable deployment of assistants across frontend, backend, and ML components.

Skills

Python

LLMs

Agentic AI

Distributed systems

Leadership

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

Tools

LangChain

LangGraph

CAMEL

AutoGen

LlamaIndex

Job description

Chamberlain Group is seeking an experienced AI software engineer to architect and build LLM-based agents that integrate with real-world tools and APIs. You will design systems that orchestrate tasks across roles and scale in production environments.

You will lead cross‑functional teams, drive tooling decisions, and mentor engineers in AI-native patterns, with a focus on reliability, observability, and fast-paced delivery within a large, established company.