Zoox is seeking an AI Solutions Architect who will be the primary driver for the design, development, and deployment of Generative AI (GenAI) and Large Language Model (LLM) solutions. You will work across the enterprise—partnering with Procurement, Legal, Finance, HR, and Marketing—to build intelligent agents and automated workflows that transform how our employees work and how our business makes decisions.

Zoox is seeking an AI Solutions Architect who will be the primary driver for the design, development, and deployment of Generative AI (GenAI) and Large Language Model (LLM) solutions. You will work across the enterprise—partnering with Procurement, Legal, Finance, HR, and Marketing—to build intelligent agents and automated workflows that transform how our employees work and how our business makes decisions.

In this role, you will:

Lead the development and deployment of AI-powered platforms and tools that enhance productivity across core business functions such as Finance, HR, IT, Marketing, Procurement, and Supply Chain.

Identify, evaluate, and implement off-the-shelf AI agents to streamline operations, reduce costs, and accelerate business processes.

Architect and deploy enterprise-grade LLM applications (RAG, Fine-tuning, Agentic workflows) to automate complex processes.

Act as the technical consultant for non-technical leads in Finance (forecasting), Legal (contract analysis), HR (talent matching), and Marketing (content personalization).

Build autonomous AI agents capable of navigating multi-step business tasks with minimal human intervention.

Collaborate with the Data Analytics team to ensure all AI deployments adhere to strict data privacy, security, and "responsible AI" standards.

Manage the lifecycle of AI products from prompt engineering and model selection (GPT-4, Claude, Llama 3, etc.) to integration with internal APIs and databases.

Qualifications:

8+ years in Data Engineering, Software Engineering, or Data Science, with at least 2+ years of hands-on experience deploying GenAI/LLMs in a production enterprise environment.

Deep proficiency in Python and frameworks such as LangChain, LlamaIndex, or AutoGen.

Experience with cloud AI services (AWS Bedrock, or Google Vertex AI) and vector databases (Pinecone, Weaviate, Milvus or OpenSearch).

Experience building agents and AI workflows.

Proven ability to translate "business pain" into "technical requirements." You need to speak "Legal" and "Finance" as fluently as you speak "Python."

AI Enterprise Architect Lead