Job description

Zoox is seeking a highly motivated, hands-on Lead AI Engineer to spearhead the end-to-end development and deployment of our Enterprise Gen AI and LLM initiatives, building agentic workflows, integrating enterprise data sources, and enforcing identity-aware security, that transform operations across Procurement, Supply Chain, Legal, Finance, HR and Manufacturing (MES). In this role, you will: Design and deploy production-grade LLM applications and intelligent agents capable of complex reasoning, secure tool usage and autonomous multi-step workflows. Architect enterprise data/tool integrations using MCP servers, establishing standardized, reusable connectors across Procurement, Supply Chain, Legal, Finance, HR and Manufacturing (MES). Enforce security guardrails via AI gateways - authentication, rate-limiting, logging and policy compliance for all model/agent traffic. Implement identity inheritance via SSO, ensuring agents act strictly within the requesting user's permissions & privileges (no privilege escalation, no standing overreach). Work with the Information Security team on access control (RBAC/ABAC) for agentic systems and establish observability standards for agent behavior and data access. Partner with cross-functional teams to build secure, code-driven AI automation. Qualifications: 10+ years in Data/Software Engineering, with 2+ years deploying GenAI/LLMs in production. Deep Python proficiency; experience with LangChain, LlamaIndex or provider-native orchestration (e.g., Claude Agent SDK, OpenAI Assistants/Agents SDK or hand-rolled). Hands-on experience building/integrating MCP servers or comparable connector frameworks. Experienced in AI gateway solutions (e.g. Cloudflare AI Gateway) for governing agent traffic. Working knowledge of SSO/identity federation (SAML, OIDC, OAuth 2.0) and propagating identity through agentic tool calls. Experience with cloud AI services (AWS Bedrock, Google Vertex AI) and vector databases (MongoDB, Pinecone, Weaviate, Milvus, OpenSearch). Bonus Qualifications: Experience building AI solutions for corporate functions like Finance, Legal (e.g. contract analysis), HR (e.g. policy retrieval), Supply Chain (e.g. forecasting efficiency) or Manufacturing (e.g., MES data integration, production/quality analytics) Familiarity with AI platform vendor evaluations (Bedrock, Vertex, Cortex, etc.) Experience defining enterprise IAM integration patterns (Okta, Entra ID, Ping) for AI systems and establishing AI governance frameworks or centers of excellence Previous experience in the autonomous vehicle, robotics or high-tech manufacturing sectors. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

Requirements

Must-haves

Design and deploy production-grade LLM applications and intelligent agents capable of complex reasoning, secure tool usage and autonomous multi-step workflows.
Architect enterprise data/tool integrations using MCP servers, establishing standardized, reusable connectors across Procurement, Supply Chain, Legal, Finance, HR and Manufacturing (MES).
Enforce security guardrails via AI gateways - authentication, rate-limiting, logging and policy compliance for all model/agent traffic.
Implement identity inheritance via SSO, ensuring agents act strictly within the requesting user's permissions & privileges (no privilege escalation, no standing overreach).
Work with the Information Security team on access control (RBAC/ABAC) for agentic systems and establish observability standards for agent behavior and data access.
Partner with cross-functional teams to build secure, code-driven AI automation.
10+ years in Data/Software Engineering, with 2+ years deploying GenAI/LLMs in production.
Deep Python proficiency; experience with LangChain, LlamaIndex or provider-native orchestration (e.g., Claude Agent SDK, OpenAI Assistants/Agents SDK or hand-rolled).
Hands-on experience building/integrating MCP servers or comparable connector frameworks.
Experienced in AI gateway solutions (e.g. Cloudflare AI Gateway) for governing agent traffic.
Working knowledge of SSO/identity federation (SAML, OIDC, OAuth 2.0) and propagating identity through agentic tool calls.
Experience with cloud AI services (AWS Bedrock, Google Vertex AI) and vector databases (MongoDB, Pinecone, Weaviate, Milvus, OpenSearch).
Familiarity with AI platform vendor evaluations (Bedrock, Vertex, Cortex, etc.)
Experience defining enterprise IAM integration patterns (Okta, Entra ID, Ping) for AI systems and establishing AI governance frameworks or centers of excellence
Previous experience in the autonomous vehicle, robotics or high-tech manufacturing sectors.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmpythonawsmachine learning

Platform: lever
Effort: quick