Principal, Product Manager - AI / LLM

Twilio is a company focused on shaping the future of communications through innovative solutions and a remote-first culture. They are seeking a Principal Product Manager to lead the development of backend services and AI platforms that enhance customer interactions by providing proactive assistance and improving the overall user experience.

Responsibilities:

• Design the "Twilio Brain": Lead the strategy for backend services that aggregate Twilio’s proprietary data (docs, support tickets, API logs) into a unified knowledge layer for our internal agents
• Drive Proactive Engagement: Define the logic and triggers for AI "nudges"—real-time, backend-driven interventions that guide customers when they encounter errors or configuration hurdles
• Omnichannel Agent Orchestration: Ensure the Copilot backend provides a consistent "memory" and personality for agents, whether the customer is interacting via the Console, SMS, or Slack
• Optimize Agent Accuracy: Establish the frameworks for RAG (Retrieval-Augmented Generation) and fine-tuning to ensure the Copilot provides technically accurate, "hallucination-free" advice on Twilio’s complex product suite
• Cross-Functional Integration: Partner with Product, Engineering, and Growth teams to embed intelligent assistance directly into the core user flows of every Twilio product
• Performance & Reliability: Manage the infrastructure costs and latency of LLM calls to ensure that Twilio’s agents respond in real-time without compromising the snappiness of the Console

Requirements:

• Extensive Experience: 8+ years of Product Management experience, with a focus on backend services, internal platforms, or intelligent automation
• Contextual AI Expertise: Deep understanding of how to build AI systems that utilize contextual data (user state, account history, real-time logs) to provide relevant, personalized assistance
• Experience with RAG & Tooling: Familiarity with building RAG pipelines and giving agents 'tools' (e.g., the ability to look up a customer's recent SID errors or billing status) to solve problems
• Growth-Oriented Mindset: Proven ability to use AI to drive business metrics like time-to-first-hello, churn reduction, and support ticket deflection
• Technical Acumen: Ability to design backend systems that can handle high-concurrency AI interactions while maintaining strict data privacy and security
• Storytelling & Influence: Experience convincing product teams to integrate centralized AI services into their specific product silos
• Conversational UX for Tech: Experience building chatbots or assistants specifically for technical/developer personas (e.g., GitHub Copilot, AWS Q)
• Behavioral Analytics: Experience using data to identify 'friction points' in a user journey and designing automated interventions to solve them
• Multi-Modal Experience: Knowledge of how to transition a customer conversation from a web-based chat to a live support ticket or a phone call with full context