2 months ago
Base Salary
$276k - $406k/yr
Responsibilities
- Define and drive Twilio’s long-term AI/ML architectural vision for data- and memory-powered customer engagement.
- Own the strategic roadmap for the company-wide ML/AI Ops platform and tooling across model development, deployment, and lifecycle management.
- Evaluate and implement LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques.
- Lead the architecture of agentic AI systems covering orchestration, reasoning, tool usage, and contextual grounding.
- Track advances in LLMs, agent frameworks, reasoning systems, and AI infrastructure.
- Move between executive-level technical communication and hands-on code reviews and pair programming with engineers.
- Partner with Product Management to translate roadmaps into technical milestones tied to customer value.
- Provide hands-on technical contributions, strategic direction, and mentorship as a player-coach.
- Serve as a Distinguished Engineer and AI Contextual Engineering subject matter expert, guiding architects and influencing company-wide technical direction.
Requirements
- 15+ years of software engineering experience, including at least 6+ years building and scaling production-grade ML systems at a platform level.
- Extensive experience with ML Ops and LLM Ops patterns, including evaluation metrics, automated retraining loops, and monitoring non-deterministic AI features at scale.
- Deep expertise in production ML/AI system design, architecture, and deployment, including transformer models, LLM orchestration, embedding models, inference optimization, and vector stores.
- Deep understanding of Context Engineering, including semantic retrieval, contextual compression, and multi-turn conversation state management.
- Experience building cloud-based services using AWS, GCP, or Azure and managing high-volume data and various data stores.
- Ability to mentor engineers, influence company-wide technical strategy and product direction, and drive cross-company results.
- Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field.
- Relevant publications at top ML conferences or significant open-source contributions are desired.
- Experience designing context-quality evaluation frameworks and enterprise-scale ML/AI Ops platforms is desired.
- Experience working in a geographically distributed environment is desired.
Benefits
- Remote role based in the United States
- Approximately 5% travel anticipated
- Healthcare insurance
- 401(k) retirement account
- Paid sick time
- Paid personal time off
- Paid parental leave
- Wellness leave and retirement savings program
- Volunteer and donation support