Staff Engineer, Software - GenAI
About The Position
Chamberlain Group is hiring a Staff Engineer, Software - GenAI to architect and build LLM-based agents that integrate with real-world tools and APIs, orchestrate tasks across roles, and scale in production. The role supports the company's shift toward AI-native experiences using foundation models. The position oversees the design, development, and deployment of AI features for Chamberlain products, including video-based search, chatbot interfaces, AI-generated insights, and backend pipelines and APIs. It develops agentic systems using LLMs, retrieval-augmented generation (RAG), MCP, tool integration, and orchestration frameworks; creates role-based architectures for agent collaboration; and develops reasoning, planning, and long-term memory capabilities. The engineer works with product, engineering, and AI research teams to deliver scalable assistants, and leads technical decisions on tooling, infrastructure, observability, and production readiness. The role also mentors engineers, supports end-to-end delivery across frontend, backend, and ML components, defines engineering workflows and coding standards, contributes to roadmap and sprint planning, and tracks delivery quality and GenAI tool adoption. Travel up to 10% domestically and internationally is required.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- 10+ years of software engineering experience, including 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 experience with agent orchestration frameworks such as LangGraph, CAMEL, or AutoGen.
- Experience leading cross-functional initiatives in AI productization, intelligent automation, or AI-native user interfaces.
- Deep understanding of agentic system design and modern AI system architecture.
- Strong programming skills in Python and experience with production software development.
- Proficiency with LLM development and orchestration tools such as LangChain, LangGraph, CAMEL, LlamaIndex, or AutoGen.
- Expertise in agent reasoning, multi-agent coordination, and role-based task decomposition.
- Working knowledge of RAG, memory systems, and API-driven tool use.
- Familiarity with vector databases such as FAISS, Weaviate, or Pinecone, and embedding techniques.
- Strong grasp of software architecture, distributed systems, and system integration principles.
- Ability to balance rapid prototyping with scalable production deployment.
- Knowledge of chatbot frameworks such as LangChain, Rasa, or custom pipelines.
- Proficiency with modern backend technologies, including Python, Node.js, and REST/gRPC APIs.
- Cloud-native development experience with GCP, AWS, or Azure.
- Experience with MLOps and model deployment pipelines.
- Excellent communication and people leadership skills.
- Comfort 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.
- Prior experience in autonomous systems, virtual assistants, or cognitive agents.
- Experience with video intelligence systems or computer vision.
- Master’s degree in Computer Science, Computer Engineering, or a related field.
- Experience in IoT, software services, video, and AI.
- Experience with consumer electronics or smart home companies.
Responsibilities
- Oversee the design, development, and deployment of AI features, including video-based search, chatbot interfaces, AI-generated insights, and backend pipelines and APIs.
- Architect and build agentic AI systems using LLMs, RAG, MCP, tool integration, and orchestration frameworks.
- Design role-based architectures for agent collaboration using coordination protocols and memory management.
- Build, test, and optimize pipelines using tools such as LangChain, LangGraph, and CAMEL.
- Develop agent reasoning, planning, and long-term memory retrieval for contextual conversations and task execution.
- Collaborate with product, engineering, and AI research teams to ensure scalable and performant deployment of assistants.
- Drive decisions about tooling, infrastructure, observability, and production readiness.
- Mentor engineers in AI-native engineering patterns, architecture, and LLM ecosystem developments.
- Ensure end-to-end delivery across frontend, backend, and ML components, promoting code quality, scalability, and maintainability.
- 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; managers should also ensure team compliance.
- Protect confidential information and Chamberlain Group’s reputation.
- Maintain professional and technical knowledge through education, publications, networking, and professional societies.
- Contribute to team projects and related work as needed.
- Travel up to 10% domestically and internationally.
Benefits
- Comprehensive benefits package, subject to eligibility requirements.
- 401k contribution, subject to eligibility requirements.
- Eligibility to participate in a short-term incentive plan, subject to applicable plan terms and policies.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
