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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Engineer, Software - GenAI (Hybrid) - **Company:** Chamberlain Group - **Location:** Oak Brook, IL, United States - **Experience:** Expert - **Salary:** $85,500.0 - $162,975.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Encodings, Computer Engineering, Distributed Systems, Python (Programming Language), Machine Learning, Scrum Methodology, Software Architecture, Software Engineering, Google Cloud, Chatbots, Large Language Models, Backend, Kubernetes, Information Technology, Enterprise Integration, Machine Learning Operations, Front End Software Development, Virtual Agents - **Published:** June 17, 2026 - **Apply:** https://chamberlain.wd1.myworkdayjobs.com/Chamberlain_Group/job/Oak-Brook-IL/Sr-Engineer--Software---GenAI--Hybrid-_JR30976 ## About the Role * Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field. * 8+ years of experience in software engineering, with at least 1+ years working with LLMs or agentic AI systems. Knowledge, Skills, and Abilities: * Strong working knowledge of agentic system concepts, modern AI components, and LLM-based workflows. * Proficiency in Python and experience supporting production-grade development. * Hands-on experience with LLM orchestration tools (e.g., LangChain, LangGraph, LlamaIndex, CAMEL) for analysis and workflow testing. * Understanding of agent reasoning, coordination patterns, memory systems, and RAG pipelines. * Experience with vector databases (FAISS, Pinecone, Weaviate) and embedding-based retrieval analysis. * Solid grasp of software architecture basics, distributed system concepts, and integration considerations. * Ability to support prototyping efforts and identify early scalability or deployment considerations. * Experience with chatbot frameworks (e.g., LangChain, Rasa) and backend integration workflows. * Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps/model deployment practices. * Strong communication and cross-team collaboration skills in fast-paced environments. Other: * Ability to travel up to 10% of the time domestically and internationally Preferred Job Requirements: * 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 * Familiarity with video foundation models, multimodal LLM and/or video summarization use cases. ## Description This is a role within CG's Engineering group. A successful incumbent is expected to (i) Contribute to planning and scoping of agentic AI systems by evaluating models, frameworks, and integration options, and by assisting engineering teams with technical analysis and workflow recommendations., and (ii) Assist and build agentic AI systems using LLMs, RAG, MCP, tool integration, and orchestration frameworks., * Contribute to planning and scoping of agentic AI systems by evaluating models, frameworks, and integration options, and by assisting engineering teams with technical analysis and workflow recommendations. * Assist and build agentic AI systems using LLMs, RAG, MCP, tool integration, and orchestration frameworks. * Conduct analysis and experimentation on agent reasoning, planning, and memory behaviors, providing insights that guide improvements to contextual interactions and task execution. * Build, test, and optimize pipelines using tools such as LangChain, LangGraph, and CAMEL. * Collaborate with product, engineering, and research teams to gather requirements, validate assumptions, and support planning for scalable and performant assistant deployments. * Prepare assessments and recommendations on tooling, infrastructure, observability, and readiness considerations to support Lead-level decision making. * Provide guidance to teams by sharing insights on AI-native engineering patterns and emerging LLM ecosystem trends, supporting knowledge transfer across groups. * Support end-to-end delivery by coordinating across frontend, backend, and ML teams, monitoring progress, and highlighting risks or quality concerns for resolution. * Contribute technical analysis and inputs to roadmap discussions and sprint planning, ensuring requirements and constraints are surfaced clearly. * Support the development and refinement of engineering workflows, coding standards, and agile practices by providing data, observations, and improvement recommendations. Assist in monitoring delivery metrics and GenAI tool usage. * 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. ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Beyond Chatbots: How to build Agentic AI systems](https://www.wearedevelopers.com/videos/1629-beyond-chatbots-how-to-build-agentic-ai-systems) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)