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Job Description
Structured overview of role & requirementsAbout This Role
Architect and own multi-agent AI systems for automotive dealership workflows, including customer-facing voice/chat agents and internal business automation agents.
Lead end-to-end agentic system lifecycle: design, orchestration, evaluation, deployment, observability, and continuous improvement.
Ensure strict accuracy and safety of agent outputs grounded in live business data, implementing guardrails and compliance for real-time conversational AI.
Minimum Requirements
8+ years of professional experience, including 2+ years specifically with production large language model (LLM) multi-agent systems.
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Proven experience designing and shipping multi-agent architectures involving orchestrators, agent topologies, planner-executor-critic loops, and failure isolation.
Strong expertise with multi-agent AI frameworks (e.g., LangGraph, OpenAI Agents SDK), frontier LLM APIs (OpenAI GPT-5.x, Anthropic Claude, Google Gemini), and realtime voice AI technologies.
Ideal Candidate Profile
Experienced in architecting complex multi-agent AI systems integrating frontend voice/chat and backend autonomous agents with real-time data grounding and safety controls.
Skilled in both engineering leadership and hands-on development using Python, TypeScript, and cloud-native platforms (preferably GCP).
Able to translate complex business workflows into scalable AI orchestration, lead cross-functional collaboration, and establish AI evaluation and operational best practices.