Twilio is a remote-first communications platform serving hundreds of thousands of businesses and millions of developers.
Responsibilities
Define and drive a long-term AI/ML architectural vision aligned with Twilio's business goals, focusing on data and memory for customer engagement.
Own the strategic roadmap for Twilio's ML/AI Ops platform and tooling.
Evaluate and implement modern LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques.
Lead architecture for agentic AI systems including orchestration, reasoning, tool usage, and contextual grounding.
Stay current with advancements in LLMs, agent frameworks, reasoning systems, and AI infrastructure.
Partner with Product Management to turn roadmaps into technical milestones.
Act as a player-coach, contributing hands-on technical expertise while mentoring the team.
Requirements
15+ years of software engineering experience, with 6+ years building and scaling production-grade ML systems at platform level.
Extensive experience with ML Ops and LLM Ops patterns, evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features.
Deep expertise in transformer models, LLM orchestration, embedding models, inference optimization, and vector stores.
Understanding of Context Engineering lifecycle: semantic retrieval, contextual compression, state management across multi-turn conversations.
Strong background in cloud-based services using AWS, GCP, or Azure.
Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or related field.
Conditions
Remote-first work with occasional in-person team gatherings, off-sites, or customer meetings.