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.
Job 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.
Job 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.
- 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.
Knowledge, Skills, and Abilities:
- Deep understanding of agentic system design and modern AI system architecture.
- 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.
- Chatbot frameworks (e.g., LangChain, Rasa, custom pipelines)
- 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
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
The pay range for this position is $126,198.00 - $215,291.00; base pay offered may vary depending on a number of factors including, but not limited to, the position offered, location, education, training, and/or experience. In addition to base pay, also offered is a comprehensive benefits package and 401k contribution (all benefits are subject to eligibility requirements). This position is eligible for participation in a short-term incentive plan subject to the terms of the applicable plans and policies.
