Technical Lead, AI Engineering Sales, Service & Supply Chain

Overview
In this role you set the technical direction for AI-enabled enterprise operations at Lucid, shaping systems that support sales, service, and supply chain. You lead a distributed engineering team to deliver production-ready solutions, balancing practicality with ambitious AI capabilities. You will design guardrails, governance, and integration with core business systems, driving measurabl
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e value early and often. This opportunity lets you influence how AI is deployed at scale in a cutting-edge automotive context.
Compensation / Benefits
• medical, dental, and vision insurance
• life and disability coverage
• paid time off and holidays
• 401(k) retirement plan
• equity program
• discretionary annual cash incentive program
Responsibilities
• Own architecture for LLM-based and agented systems across Sales, Service and Supply Chain
• Deliver AI solutions through web, in-app chat, email, and SMS channels
• Translate business problems into engineering plans and drive early value
• Build safety and governance features for enterprise AI (guardrails, identity, prompt governance)
• Own tool layer and contracts for agent delivery (versioning, permissions, testing)
• Define quality metrics and establish production testing and telemetry
• Manage cost and latency targets across routing, caching, and retrieval
• Integrate AI with ERP, supplier portals, service and CRM platforms
• Set standards and reusable patterns for the team
• Provide cross-time-zone technical leadership and mentorship
• Assess and communicate where AI helps or not to avoid detours
Key requirements
• 10+ years building and operating production software
• 3+ years owning technical direction of a team or platform
• Strong Python and distributed systems fundamentals
• Production experience with LLM applications: RAG, agents, tool-calling, streaming, prompts
• Hands-on experience with LLM tooling (Langfuse, LangSmith) for tracing and monitoring
• Experience with MCP servers, tool schemas, authentication and permissions
• Cost optimization for AI: routing, context trimming, batching, caching, token budgeting
• Experience delivering AI over chat, email, SMS and related integrations
• Judgment on model landscape and cost/latency/accuracy trade-offs
• Strong AWS engineering experience or equivalent
• Data layer experience (relational, document, vector) and retrieval accuracy
• Ability to translate business intent to system design and communicate with non-technical stakeholders
• Mentorship and leadership across distributed teams
• Strong collaboration with business stakeholders
• Clear communication and stakeholder management
• Python
• Distributed systems
• LLM applications (RAG, agents, tool-calling)

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