Staff Software Engineer - GenAI

Chamberlain Group•Oak Brook, IL

About The Position

This role is a cornerstone in our shift toward AI-native experiences — moving beyond traditional ML and into systems that reason, act, and collaborate autonomously using foundation models. This role will be responsible for architecting and building LLM-based agents that integrate with real-world tools and APIs, orchestrate tasks across roles, and scale intelligently in production environments.

Requirements

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
10+ years of experience in software engineering, with at least 2+ years working with LLMs or agentic AI systems.
Proven experience building LLM-powered agents that interact with external tools and APIs.
Demonstrated work with agent orchestration frameworks (e.g., LangGraph, CAMEL, AutoGen).
Experience leading cross-functional initiatives in AI productization, intelligent automation, or AI-native user interfaces.
Strong programming skills in Python and experience with production software development.
Proficiency in LLM-based development and orchestration tools: LangChain, LangGraph, CAMEL, LlamaIndex, AutoGen, or similar.
Expertise in agent reasoning, multi-agent coordination, and role-based task decomposition.
Working knowledge of retrieval-augmented generation (RAG), memory systems, and API-driven tool use.
Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding techniques.
Strong grasp of software architecture, distributed systems, and system integration principles.
Ability to balance rapid prototyping with scalable production deployment.
Proficiency with modern backend technologies (Python, Node.js, REST/gRPC APIs).
Cloud-native development experience (GCP, AWS, or Azure).
Experience working with MLOps and model deployment pipelines.
Excellent communication and people leadership skills.
Comfortable operating in a fast-paced, startup-like environment within an established company.

Nice To Haves

Experience in AI infrastructure, prompt engineering, or fine-tuning LLMs is a strong plus.
Prior experience working in autonomous systems, virtual assistants, or cognitive agents is highly desirable.
Video intelligence systems, Computer Vision is a strong plus.
Chatbot frameworks (e.g., LangChain, Rasa, custom pipelines)
Master’s degree in Computer Science, Computer Engineering, or related field.
Experience in IoT, software services, video, and AI.
Experience with consumer electronics, smart home companies will be beneficial.

Responsibilities

Oversee the design, development, and deployment of AI features within Chamberlain products such as: Video-based search using LLMs, Chatbot interfaces for search and AI-generated insight, backend pipelines and APIs for AI feature delivery.
Architect and build agentic AI systems using LLMs, RAG, MCP, tool integration, and orchestration frameworks.
Design role-based architectures where agents collaborate through coordination protocols and memory management.
Build, test, and optimize pipelines using tools such as LangChain, LangGraph, and CAMEL.
Develop systems for agent reasoning, planning, and long-term memory retrieval to enable contextual conversations and task execution.
Work across product, engineering, and AI research teams to ensure scalable and performant deployment of assistants.
Drive decision-making around tooling, infrastructure, observability, and production-readiness.
Mentor engineers across the org in AI-native engineering patterns, architecture, and LLM ecosystem evolution.
Ensure end-to-end delivery across frontend, backend, and ML components, and drive code quality, scalability, and maintainability best practices.
Act as the technical voice in roadmap discussions and sprint planning.
Define engineering workflows, coding standards, and agile practices.
Track and improve delivery velocity, quality metrics, and GenAI tool adoption.
Comply with health and safety guidelines and rules; managers should also ensure compliance across their teams.
Protect Chamberlain Group’s reputation by keeping information confidential.
Maintain professional and technical knowledge by attending educational workshops, reading professional publications, establishing personal networks, and participating in professional societies.
Contribute to the team effort by accomplishing related results and participating on projects as needed.