Conversational AI Lead for Sales & Growth

Rivian; Palo Alto (CA); On-site; USD 154,000 - 193,000; Full time

Job summary

Rivian is refining its operating model for enterprise AI agents that engage customers intelligently across milestones from inquiry to ownership. You will own the conversation logic, customer-journey mapping, and performance optimization of AI agents across touchpoints.

This platform owner role sits within the Sales organization, bridging sales enablement and AI execution. You will translate capabilities into sales value by improving prompts, tool-calling logic, and evaluating agent performance

Qualifications

• 7+ years of technical sales/revenue operations experience, or software engineering, or AI operations, with proficiency in TypeScript or JavaScript (Node.js).
• Hands-on experience evaluating LLMs, understanding how models reason and fail.
• Comfortable reading REST API specs and working with JSON Schemas provided by technical teams.
• Ability to translate business goals (lead qualification, response time reduction, conversion) into deterministic agent code.
• Deep understanding of sales funnels, customer journeys, frontline workflows, and the operational levers that influence conversion and customer satisfaction.
• Strong executive presence required with experience successfully presenting and distilling complex concepts for a C-suite audience.
• Experience explaining technical concepts (prompting, tool calling, model behavior) to non-technical stakeholders and vice versa.
• Exceptional conversational writing skills: able to craft concise, natural, and persuasive dialogue that aligns with brand tone and voice.
• Demonstrated ability to define product strategy and translate ambiguous business problems into prioritized roadmaps and executable requirements.

Responsibilities

• Define conversation logic, decision policies, and behavioral guardrails for AI agents across customer scenarios and journeys, enabling reliable, effective behavior at scale.
• Map customer journeys through the agent: define decision points, routing logic, qualification criteria, and handoff conditions that optimize for lead quality, conversion, and customer experience.
• Define the metrics that matter for agent performance: conversation completion rates, lead quality scores, customer satisfaction, routing accuracy, time-to-resolution, and impact on sales pipeline.
• Partner with Analytics/Commercial Technology to build dashboards that surface agent performance at multiple levels: daily operations view, weekly performance trends, and monthly business impact analysis.
• Present channel performance, risk, and roadmap updates in a recurring cadence (e.g. weekly ops review, monthly business review), translating technical detail into clear narratives for an executive audience.
• Diagnose model behavior, tool-use failures, instruction conflicts, and workflow breakdowns using transcripts and evaluation data.
• Run A/B tests on agent behavior changes; measure impact on conversation quality, customer satisfaction, lead routing accuracy, and sales outcomes.
• Treat agent optimization as a continuous process, not a one-time build. Conduct regular analysis of agent conversations and surface improvement opportunities.
• Serve as the primary escalation point for agent-related issues, coordinating cross-functional triage and root cause analysis.
• Communicate with field teams and cross-functional stakeholders to understand improvements with most impact.
• Drive progress in ambiguous, cross-functional environments and remove barriers to execution through clear decisions.

Skills

5G? no

Tools

LangChain

CrewAI

Job description

Rivian is refining its operating model for enterprise AI agents that engage customers intelligently across milestones from inquiry to ownership. You will own the conversation logic, customer-journey mapping, and performance optimization of AI agents across touchpoints.

This platform owner role sits within the Sales organization, bridging sales enablement and AI execution. You will translate capabilities into sales value by improving prompts, tool-calling logic, and evaluating agent performance